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  • 1.
    Abarghouyi, Hadis
    et al.
    IUST, Iran; MTNi Co, Iran.
    Razavizadeh, S. Mohammad
    IUST, Iran.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    QoE-Aware Beamforming Design for Massive MIMO Heterogeneous Networks2018In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 67, no 9, p. 8315-8323Article in journal (Refereed)
    Abstract [en]

    One of the main goals of the future wireless networks is improving the users quality of experience (QoE). In this paper, we consider the problem of the QoE-based resource allocation in the downlink of a massive multiple-input multiple-output heterogeneous network. The network consists of a macrocell with a number of small cells embedded in it. The small cells base stations (BSs) are equipped with a few antennas, while the macro BS is equipped with a massive number of antennas. We consider the two services Video and Web Browsing and design the beamforming vectors at the BSs. The objective is to maximize the aggregated mean opinion score (MOS) of the users under constraints on the BSs powers and the required quality of service of the users. We also consider extra constraints on the QoE of users to more strongly enforce the QoE in the beamforming design. To reduce the complexity of the optimization problem, we suggest suboptimal and computationally efficient solutions. Our results illustrate that increasing the number of antennas at the BSs and also increasing the number of small cells antennas in the network leads to a higher user satisfaction.

  • 2.
    Abrahamsson, Olle
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Hide and Seek in a Social Network2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In this thesis a known heuristic for decreasing a node's centrality scores while maintaining influence, called ROAM, is compared to a modified version specifically designed to decrease eigenvector centrality. The performances of these heuristics are also tested against the Shapley values of a cooperative game played over the considered network, where the game is such that influential nodes receive higher Shapley values. The modified heuristic performed at least as good as the original ROAM, and in some instances even better (especially when the terrorist network behind the World Trade Center attacks was considered). Both heuristics increased the influence score for a given targeted node when applied consecutively on the WTC network, and consequently the Shapley values increased as well. Therefore the Shapley value of the game considered in this thesis seems to be well suited for discovering individuals that are assumed to actively trying to evade social network analysis.

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    fulltext
  • 3.
    Abrahamsson, Olle
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Danev, Danyo
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Opinion Dynamics with Random Actions and a Stubborn Agent2019In: CONFERENCE RECORD OF THE 2019 FIFTY-THIRD ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS & COMPUTERS, IEEE , 2019, p. 1486-1490Conference paper (Refereed)
    Abstract [en]

    We study opinion dynamics in a social network with stubborn agents who influence their neighbors but who themselves always stick to their initial opinion. We consider first the well-known DeGroot model. While it is known in the literature that this model can lead to consensus even in the presence of a stubborn agent, we show that the same result holds under weaker assumptions than has been previously reported. We then consider a recent extension of the DeGroot model in which the opinion of each agent is a random Bernoulli distributed variable, and by leveraging on the first result we establish that this model also leads to consensus, in the sense of convergence in probability, in the presence of a stubborn agent. Moreover, all agents opinions converge to that of the stubborn agent.

  • 4.
    Abrahamsson, Olle
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Danev, Danyo
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Structural Balance Considerations for Networks with Preference Orders as Node Attributes2022In: 2022 56TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, IEEE , 2022, p. 1255-1261Conference paper (Refereed)
    Abstract [en]

    We discuss possible definitions of structural balance conditions in a network with preference orderings as node attributes. The main result is that for the case with three alternatives (A, B, C) we reduce the (3!)(3) = 216 possible configurations of triangles to 10 equivalence classes, and use these as measures of balance of a triangle towards possible extensions of structural balance theory. Moreover, we derive a general formula for the number of equivalent classes for preferences on n alternatives. Finally, we analyze a real-world data set and compare its empirical distribution of triangle equivalence classes to a null hypothesis in which preferences are randomly assigned to the nodes.

  • 5.
    Ahlqvist, Johan
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Evaluation of the Turbo-decoder Coprocessor on a TMS320C64x Digital Signal Processor2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    One technique that is used to reduce the errors brought upon signals, when transmitted over noisy channels, is error control coding. One type of such coding, which has a good performance, is turbo coding. In some of the TMS320C64xTM digital signal processors there is a built in coprocessor that performs turbo decoding.

    This thesis is performed on the account of Communication Developments, within Saab AB and presents an evaluation of this coprocessor. The evaluation deals with both the memory consumption as well as the data rate. The result is also compared to an implementation of turbo coding that does not use the coprocessor.

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    Evaluation of Turbo Decoding on DSP
  • 6.
    Ahmad, Shakeel
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering. Univ Management and Technol, Pakistan.
    Dabrowski, Jerzy
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Design of Two-Tone RF Generator for On-Chip IP3/IP2 Test2019In: Journal of electronic testing, ISSN 0923-8174, E-ISSN 1573-0727, Vol. 35, no 1, p. 77-85Article in journal (Refereed)
    Abstract [en]

    In this paper a built-in-self-test (BiST) aimed at the third and second intercept point (IP3/IP2) characterization of RF receiver is discussed with a focus on a stimulus generator. The generator is designed based on a specialized phase-lock loop (PLL) architecture with two voltage controlled oscillators (VCOs) operating in GHz frequency range. The objective of PLL is to keep the VCOs frequency spacing under control. According to the test requirements the phase noise and nonlinear distortion of the two-tone generator are considered as a merit for the design of VCOs and analog adder. The PLL reference spurs, critical for the IP3 measurement, are avoided by means of a frequency doubling technique. The circuit is designed in 65nm CMOS. A highly linear analog adder with OIP3amp;gt;+15dBm and ring VCOs with phase noise amp;lt; -104 dBc/Hz at 1MHz offset are used to generate the RF stimulus of total power greater than -22dBm. In simulations a performance sufficient for IP3/IP2 test of a typical RF CMOS receiver is demonstrated.

  • 7.
    Ahmad, Shakeel
    et al.
    Linköping University, Department of Electrical Engineering. Linköping University, Faculty of Science & Engineering. Univ Management & Technol, Pakistan.
    Dabrowski, Jerzy
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    One-Bit Sigma Delta-Encoded Stimulus Generation for On-Chip ADC Test2020In: Journal of Circuits, Systems and Computers, ISSN 0218-1266, Vol. 29, no 15, article id 2050245Article in journal (Refereed)
    Abstract [en]

    This paper presents an application of the Sigma Delta modulation technique to the on-chip dynamic test for analog-to-digital converters (ADCs). The required stimulus such as a single- or two-tone signal is encoded into one-bit Sigma Delta sequence, which is applied to an ADC under test through a driving buffer and a simple low-pass reconstruction filter. By a systematic approach, we select the order and type of a Sigma Delta modulator and develop a frequency plan suitable for the spectral measurement. In this way, we achieve a high dynamic range suitable for spectral harmonic and intermodulation distortion tests for ADCs. For high frequency measurements (up to the Nyquist frequency), we propose a novel low-pass/band-pass modulation scheme that allows to avoid harmful effects of the low-frequency quantization noise. Also we address the distortion components which originate from the buffer imperfections for a nonreturn-to-zero waveform representing the encoded stimulus. We show that the low-frequency distortion components can be cancelled by using a simple iterative predistortion technique supported by measurements with a DC-calibrated ADC. By correlation between low- and high-frequency components also the high frequency distortions can be largely reduced. The presented techniques are illustrated by simulation results of an ADC under test.

  • 8.
    Ahmed, Atheeq
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Human Detection Using Ultra Wideband Radar and Continuous Wave Radar2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    A radar works by radiating electromagnetic energy and detecting the reflected signal returned from the target. The nature of the reflected signal provides information about the target’s distance or speed. In this thesis, we will be using a UWB radar and a CW radar to help detect the presence and rough location of trapped survivors by detecting their motions. Range is estimated in the UWB radar using clutter removal with SVD and for the dual frequency CW Radar using STFT and median filtering. The effect of the algorithm parameters on their performance was analyzed. The performance of the implemented algorithms with regards to small motion detection, distance estimation and penetration capability was analyzed. Both systems are certainly capable of human detection and tracking.

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    fulltext
  • 9.
    Ahuja, Bhawna
    et al.
    Indian Inst Technol, India.
    Mishra, Deepak
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Bose, Ranjan
    Indian Inst Technol, India; Indraprastha Inst Informat Technol, India.
    Novel QoS-Aware Physical Layer Security Analysis Considering Random Inter-node Distances2019In: ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE , 2019Conference paper (Refereed)
    Abstract [en]

    Physical layer security (PLS) in wireless communication has gained recent attention due to the emergence of new technological breakthroughs in this space. Since the internode distances have been noted to play a key role in the desired security performance, we propose a novel quality-of-service-aware PLS model that incorporates the random spatial deployment of the legitimate users and a potential attacker. This proposed model considers practical constraints like maximum separation between legitimate users and eavesdropping capability of attacker. In this regard, a novel concept of eavesdropping zone is also introduced. Eventually, closed-form expressions are derived for secrecy outage probability using the probabilistic inter-node distance distributions between the legitimate users and attacker to shed key analytical insights like optimal parameter designing to achieve a desired secrecy performance. Lastly, specific simulation results, presented to validate the analytical claims and provide key secured system designing perspectives, corroborate the potential of the proposed framework for more accurately characterizing the desired PLS performance from both the legitimate users and attackers point-of-view.

  • 10.
    Akbar, Noman
    et al.
    Australian Natl Univ, Australia.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Yang, Nan
    Australian Natl Univ, Australia.
    Downlink Power Control in Massive MIMO Networks with Distributed Antenna Arrays2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE, 2018Conference paper (Refereed)
    Abstract [en]

    In this paper, we investigate downlink power control in massive multiple-input multiple-output (MIMO) networks with distributed antenna arrays. The base station (BS) in each cell consists of multiple antenna arrays, which are deployed in arbitrary locations within the cell. Due to the spatial separation between antenna arrays, the large-scale propagation effect is different from a user to different antenna arrays in a cell, which makes power control a challenging problem as compared to conventional massive MIMO. We assume that the BS in each cell obtains the channel estimates via uplink pilots. Based on the channel estimates, the BSs perform maximum ratio transmission for the downlink. We then derive a closed-form spectral efficiency (SE) expression, where the channels are subject to correlated fading. Utilizing the derived expression, we propose a max-min power control algorithm to ensure that each user in the network receives a uniform quality of service. Numerical results demonstrate that, for the network considered in this work, optimizing for max-min SE through the max-min power control improves the sum SE of the network as compared to the equal power allocation.

  • 11.
    Akbar, Noman
    et al.
    Australian Natl Univ, Australia.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Yang, Nan
    Australian Natl Univ, Australia.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Max-Min Power Control in Downlink Massive MIMO With Distributed Antenna Arrays2021In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 69, no 2, p. 740-751Article in journal (Refereed)
    Abstract [en]

    In this paper, we investigate optimal downlink power allocation in massive multiple-input multiple-output (MIMO) networks with distributed antenna arrays (DAAs) under correlated and uncorrelated channel fading. In DAA massive MIMO, a base station (BS) consists of multiple antenna sub-arrays. Notably, the antenna sub-arrays are deployed in arbitrary locations within a DAA massive MIMO cell. Consequently, the distance-dependent large-scale propagation coefficients are different from a user to these different antenna sub-arrays, which makes power control a challenging problem. We assume that the network operates in time-division duplex mode, where each BS obtains the channel estimates via uplink pilots. Based on the channel estimates, the BSs perform maximum-ratio transmission in the downlink. We then derive a closed-form signal-to-interference-plus-noise ratio (SINR) expression, where the channels are subject to correlated fading. Based on the SINR expression, we propose a network-wide max-min power control algorithm to ensure that each user in the network receives a uniform quality of service. Numerical results demonstrate the performance advantages offered by DAA massive MIMO. For some specific scenarios, DAA massive MIMO can improve the average per-user throughput up to 55%. Furthermore, we demonstrate that channel fading covariance is an important factor in determining the performance of DAA massive MIMO.

  • 12.
    Akhlaghpasand, Hossein
    et al.
    Iran Univ Sci and Technol, Iran.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Razavizadeh, S. Mohammad
    Iran Univ Sci and Technol, Iran.
    Jamming Suppression in Massive MIMO Systems2020In: IEEE Transactions on Circuits and Systems - II - Express Briefs, ISSN 1549-7747, E-ISSN 1558-3791, Vol. 67, no 1, p. 182-186Article in journal (Refereed)
    Abstract [en]

    In this brief, we propose a framework for protecting the uplink transmission of a massive multiple-input multiple-output (mMIMO) system from a jamming attack. Our framework includes a novel minimum mean-squared error-based jamming suppression (MMSE-JS) estimator for channel training and a linear zero-forcing jamming suppression (ZFJS) detector for uplink combining. The MMSE-JS exploits some intentionally unused pilots to reduce the pilot contamination caused by the jammer. The ZFJS suppresses the jamming interference during the detection of the legitimate users data symbols. The proposed framework is implementable, since the complexities of computing the MMSE-JS and the ZFJS are linear (not exponential) with respect to the number of antennas at the base station and can be fabricated using 28-nm fully depleted silicon on insulator technology and for the mMIMO systems. Our analysis shows that the jammer cannot dramatically affect the performance of an mMIMO system equipped with the combination of MMSE-JS and ZFJS. Numerical results confirm our analysis.

  • 13.
    Akhlaghpasand, Hossein
    et al.
    Iran Univ Sci and Technol, Iran.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Razavizadeh, S. Mohammad
    Iran Univ Sci and Technol, Iran.
    Jamming-Robust Uplink Transmission for Spatially Correlated Massive MIMO Systems2020In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 68, no 6, p. 3495-3504Article in journal (Refereed)
    Abstract [en]

    In this paper, we consider how the uplink transmission of a spatially correlated massive multiple-input multiple-output (MIMO) system can be protected from a jamming attack. To suppress the jamming, we propose a novel framework including a new optimal linear estimator in the training phase and a bilinear equalizer in the data phase. The proposed estimator is optimal in the sense of maximizing the spectral efficiency of the legitimate system attacked by a jammer, and its implementation needs the statistical knowledge about the jammers channel. We derive an efficient algorithm to estimate the jamming information needed for implementation of the proposed framework. Furthermore, we demonstrate that optimized power allocation at the legitimate users can improve the performance of the proposed framework regardless of the jamming power optimization. Our proposed framework can be exploited to combat jamming in scenarios with either ideal or non-ideal hardware at the legitimate users and the jammer. Numerical results reveal that using the proposed framework, the jammer cannot dramatically affect the performance of the legitimate system.

  • 14.
    Akhlaghpasand, Hossein
    et al.
    Iran Univ Sci and Technol, Iran.
    Razavizadeh, S. Mohammad
    Iran Univ Sci and Technol, Iran.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Do, Tan Tai
    Ericsson AB, Sweden.
    Jamming Detection in Massive MIMO Systems2018In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, no 2, p. 242-245Article in journal (Refereed)
    Abstract [en]

    This letter considers the physical layer security of a pilot-based massive multiple-input multiple-output (MaMIMO) system in presence of a multi-antenna jammer. We propose a new jamming detection method that makes use of a generalized likelihood ratio tes

  • 15.
    Alesand, Elias
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Identification of Flying Drones in Mobile Networks using Machine Learning2019Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Drone usage is increasing, both in recreational use and in the industry. With it comes a number of problems to tackle. Primarily, there are certain areas in which flying drones pose a security threat, e.g., around airports or other no-fly zones. Other problems can appear when there are drones in mobile networks which can cause interference. Such interference comes from the fact that radio transmissions emitted from drones can travel more freely than those from regular UEs (User Equipment) on the ground since there are few obstructions in the air. Additionally, the data traffic sent from drones is often high volume in the form of video streams. The goal of this thesis is to identify so-called "rogue drones" connected to an LTE network. Rogue drones are flying drones that appear to be regular UEs in the network. Drone identification is a binary classification problem where UEs in a network are classified as either a drone or a regular UE and this thesis proposes machine learning methods that can be used to solve it. Classifications are based on radio measurements and statistics reported by UEs in the network. The data for the work in this thesis is gathered through simulations of a heterogenous LTE network in an urban scenario. The primary idea of this thesis is to use a type of cascading classifier, meaning that classifications are made in a series of stages with increasingly complex models where only a subset of examples are passed forward to subsequent stages. The motivation for such a structure is to minimize the computational requirements at the entity making the classifications while still being complex enough to achieve high accuracy. The models explored in this thesis are two-stage cascading classifiers using decision trees and ensemble learning techniques. It is found that close to 60% of the UEs in the dataset can be classified without errors in the first of the two stages. The rest is forwarded to a more complex model which requires more data from the UEs and can achieve up to 98% accuracy. 

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    Alesand - Identification of Flying Drones in Mobile Networks using Machine Learning
  • 16.
    Al-Hraishawi, Hayder
    et al.
    Southern Illinois Univ, IL 62901 USA.
    Baduge, Gayan Amarasuriya Aruma
    Southern Illinois Univ, IL 62901 USA.
    Ngo, Hien Quoc
    Queens Univ Belfast, North Ireland.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Multi-Cell Massive MIMO Uplink With Underlay Spectrum Sharing2019In: IEEE Transactions on Cognitive Communications and Networking, E-ISSN 2332-7731, Vol. 5, no 1, p. 119-137Article in journal (Refereed)
    Abstract [en]

    The achievable rates are investigated for multicell multi-user massive multiple-input multiple-output (MIMO) systems with underlay spectrum sharing. A general pilot sharing scheme and two pilot sequence designs (PSDs) are investigated via fully shared (PSD-1) and partially shared (PSD-2) uplink pilots. The number of simultaneously served primary users and secondary users (SUs) in the same time-frequency resource block by the PSD-1 is higher than that of PSD-2. The transmit power constraints for the SUs are derived to mitigate the secondary co-channel interference (CCI) inflicted at the primary base-station (PBS) subject to a predefined primary interference temperature (PIT). The optimal transmit power control coefficients for the SUs with max-min fairness and the common achievable rates are derived. The cumulative detrimental effects of channel estimation errors, CCI and intra-cell/inter-cell pilot contamination are investigated. The secondary transmit power constraint and the achievable rates for the perfect channel state information (CSI) case become independent of the PIT when the number of PBS antennas grows unbounded. Therefore, the primary and secondary systems can be operated independent of each other as both intra-cell and inter-cell interference can be asymptotically mitigated at the massive MIMO PBS and secondary base-station. Nevertheless, the achievable rates and secondary power constraints for the imperfect CSI case with PSD-1 are severely degraded due to the presence of intra-cell and inter-cell pilot contamination. These performance metrics depend on the PIT even in the asymptotic PBS antenna regime. Hence, the primary and secondary systems can no longer be operated independently for imperfect CSI with PSD-1. However, PSD-2 provides an achievable rate gain over PSD-1 despite the requirement of lengthier pilot sequences of the former than that of the latter.

  • 17.
    Allander, Martin
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Channel Equalization Using Machine Learning for Underwater Acoustic Communications2020Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Wireless underwater acoustic (UWA) communications is a developing field with various applications. The underwater acoustic communication channel is very special and its behavior is environment-dependent. The UWA channel is characterized by low available bandwidth, and severe motion-introduced Doppler effect compared to wireless radio communication. Recent literature suggests that machine learning (ML)-based channel estimation and equalization offer benefits over traditional techniques (a decision feedback equalizer), in UWA communications. ML can be advantageous due to the difficultly in designing algorithms for UWA communication, as finding general channel models have proven to be difficult. This study aims to explore if ML-based channel estimation and equalization as a part of a sophisticated physical layer structure can offer improved performance. In the study, supervised ML using a deep neural network and a recurrent neural network will be utilized to improve the bit error rate. A channel simulator with environment-specific input is used to study a wide range of channels. The simulations are utilized to study in which environments ML should be tested. It is shown that in highly time-varying channels, ML outperforms traditional techniques if trained with prior information of the channel. However, utilizing ML without prior information of the channel yielded no improvement of the performance.

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    fulltext
  • 18.
    Alodeh, Maha
    et al.
    Univ Luxembourg, Luxembourg.
    Spano, Danilo
    Univ Luxembourg, Luxembourg.
    Kalantari, Ashkan
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. Univ Luxembourg, Luxembourg.
    Tsinos, Christos G.
    Univ Luxembourg, Luxembourg.
    Christopoulos, Dimitrios
    Newtec Satcom, Belgium.
    Chatzinotas, Symeon
    Univ Luxembourg, Luxembourg.
    Ottersten, Bjorn
    Univ Luxembourg, Luxembourg.
    Symbol-Level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-Art, Classification, and Challenges2018In: IEEE Communications Surveys and Tutorials, E-ISSN 1553-877X, Vol. 20, no 3, p. 1733-1757Article in journal (Refereed)
    Abstract [en]

    Precoding has been conventionally considered as an effective means of mitigating or exploiting the interference in the multiantenna downlink channel, where multiple users are simultaneously served with independent information over the same channel resources. The early works in this area were focused on transmitting an individual information stream to each user by constructing weighted linear combinations of symbol blocks (codewords). However, more recent works have moved beyond this traditional view by: 1) transmitting distinct data streams to groups of users and 2) applying precoding on a symbol-persymbol basis. In this context, the current survey presents a unified view and classification of precoding techniques with respect to two main axes: 1) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding and 2) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding. Furthermore, the classified techniques are compared through representative numerical results to demonstrate their relative performance and uncover fundamental insights. Finally, a list of open theoretical problems and practical challenges are presented to inspire further research in this area.(1)

  • 19.
    Al-Salihi, Hayder
    et al.
    The Department of Informatics, King’s College London, UK.
    Van Chien, Trinh
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Le, Tuan Anh
    The Department of Design Engineering and Mathematics, Middlesex University, London, UK.
    Nakhai, Mohammad Reza
    The Department of Informatics, King’s College London, London, UK.
    A Successive Optimization Approach to Pilot Design for Multi-Cell Massive MIMO Systems2018In: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 22, no 5, p. 1086-1089Article in journal (Refereed)
    Abstract [en]

    In this letter, we introduce a novel pilot designapproach that minimizes the total mean square errors of theminimum mean square error estimators of all base stations (BSs)subject to the transmit power constraints of individual users inthe network, while tackling the pilot contamination in multicellmassive MIMO systems. First, we decompose the originalnon-convex problem into distributed optimization sub-problemsat individual BSs, where each BS can optimize its own pilotsignals given the knowledge of pilot signals from the remainingBSs. We then introduce a successive optimization approach totransform each optimization sub-problem into a linear matrixinequality form, which is convex and can be solved by availableoptimization packages. Simulation results confirm the fast convergenceof the proposed approach and prevails a benchmarkscheme in terms of providing higher accuracy.

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    fulltext
  • 20.
    Amarasuriya, Gayan
    et al.
    Princeton University, NJ 08544 USA.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Vincent Poor, H.
    Princeton University, NJ 08544 USA.
    Wireless Information and Power Transfer in Multiway Massive MIMO Relay Networks2016In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 6, p. 3837-3855Article in journal (Refereed)
    Abstract [en]

    Simultaneous wireless information and power transfer techniques for multiway massive multiple-input multiple-output (MIMO) relay networks are investigated. By using two practically viable relay receiver designs, namely 1) the power splitting receiver and 2) the time switching receiver, asymptotic signal-to-interference-plus-noise ratio (SINR) expressions are derived for an unlimited number of antennas at the relay. These asymptotic SINRs are then used to derive asymptotic symmetric sum rate expressions in closed form. Notably, these asymptotic SINRs and sum rates become independent of radio frequency-to-direct current (RF-to-DC) conversion efficiency in the limit of infinitely many relay antennas. Moreover, tight average sum rate approximations are derived in closed form for finitely many relay antennas. The fundamental tradeoff between the harvested energy and the sum rate is quantified for both relay receiver structures. Notably, the detrimental impact of imperfect channel state information (CSI) on the MIMO detector/precoder is investigated, and thereby, the performance degradation caused by pilot contamination, which is the residual interference due to nonorthogonal pilot sequence usage in adjacent/cochannel systems, is quantified. The presence of cochannel interference (CCI) can be exploited to be beneficial for energy harvesting at the relay, and consequently, the asymptotic harvested energy is an increasing function of the number of cochannel interferers. Notably, in the genie-aided perfect CSI case, the detrimental impact of CCI for signal decoding can be cancelled completely whenever the number of relay antennas grows without bound. Nevertheless, the pilot contamination severely degrades the sum rate performance even for infinitely many relay antennas.

  • 21.
    Anchora, Luca
    et al.
    IMT of Lucca.
    Badia, Leonardo
    Università degli Studi di Padova.
    Karipidis, Eleftherios
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Zorzi, Mikele
    Università degli Studi di Padova.
    Capacity Gains due to Orthogonal Spectrum Sharing in Multi-Operator LTE Cellular Networks2012In: Proceedings of the Ninth International Symposium on Wireless Communication Systems (ISWCS), 2012, p. 286-290Conference paper (Refereed)
    Abstract [en]

    Static spectrum allocation leads to resource wastage and inter-operator spectrum sharing is a possible way to improve spectrum efficiency. In this work, we assume that two cellular network operators agree upon sharing part of their spectrum, which can then be dynamically accessed by either of them in a mutually exclusive way. Our goal is to numerically assess the gain, in terms of cell capacity, due to such orthogonal spectrum sharing. Hence, we propose a centralized algorithm that performs coordinated scheduling, in order to numerically evaluate an upper bound on the achievable sum capacity. The algorithm is centralized and exploits complete information on both networks to perform the optimum allocation. The simulation results illustrate the impact of the multiuser diversity and the asymmetry in the traffic load among the networks on the overall achievable gain.

  • 22.
    Anchora, Luca
    et al.
    IMT of Lucca.
    Badia, Leonardo
    Università degli Studi di Padova.
    Zhang, Haibin
    TNO ICT.
    Fahldieck, Torsten
    Bell Labs, Alcatel-Lucent.
    Zhang, Jianshu
    Ilmenau University of Technology.
    Szydelko, Michal
    Wroclaw Research Centre EIT+ .
    Schubert, Martin
    Fraunhofer Institute for Telecommunications HHI.
    Karipidis, Eleftherios
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Haardt, Martin
    Ilmenau University of Technology.
    Resource Allocation and Management in Multi-Operator Cellular Networks with Shared Physical Resources2012In: Proceedings of the Ninth International Symposium on Wireless Communication Systems (ISWCS), IEEE , 2012, p. 296-300Conference paper (Refereed)
    Abstract [en]

    In this paper, we focus on next-generation cellular networks and discuss physical resources sharing among the operators. This implies cooperative usage of the available radio frequencies and also infrastructure sharing. In particular, we analyze the spectrum sharing gain achievable at different time scales and the main factors impacting on it. Then, we move towards a wider idea of resource sharing and consider a joint spectrum and infrastructure sharing (full sharing). We describe a two-layer resource management architecture that enables operators to reduce costs while still guaranteeing a good service level. The main findings of our investigations are to quantify the effectiveness of resource sharing and open up new perspectives for the operators of next-generation networks.

  • 23.
    Andersson, Martin
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Lidström, Andreas
    Linköping University.
    Lindmark, Gustav
    Ericsson AB, Linkoping, Sweden.
    Indoor 5G Positioning using Multipath Measurements2023In: 2023 IEEE/ION POSITION, LOCATION AND NAVIGATION SYMPOSIUM, PLANS, IEEE , 2023, p. 1092-1098Conference paper (Refereed)
    Abstract [en]

    Positioning with high precision and reliability can be provided by 5G cellular networks in environments where satellite positioning is not available or reliable. The accuracy that can be achieved by classical methods like triangulation and trilateration however degrades significantly under non line of sight (NLOS) conditions. The problem can be mitigated with increasingly dense deployments of network transmission and reception points (TRPs), but that is both impractical and costly. As an alternative, this study investigates if multipath propagation of radio signals can be exploited to improve positioning accuracy and reduce the necessary deployment density. With 3GPP Rel. 17 new signaling support has been introduced to report the propagation delay, corresponding to the length, of multiple paths between the user equipment (UE) and a network TRP. The length of a multipath can, in combination with a partially known map of the environment, give additional information about the UE position. In this study we develop multipath-assisted tracking algorithms and evaluate their performances in realistic simulations using 3GPP standardized positioning reference signals and measurements in an indoor factory environment. Our evaluations show that multipath-assisted algorithms can achieve an accuracy below 0.9 m in 90% of the cases, which is more than tenfold better than a conventional LOS based algorithm. Moreover, one algorithm variant also shows an ability to track a UE using very few TRPs.

  • 24.
    Andersson, Rickard
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Algorithm for Handoff in VDL mode 42010Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    VDL mode 4 is a digital data link operating in the VHF band, its mainly use is for the aviation industry.VDL4 can as an example provide with positioning data, speed information of aircrafts or vehicles equipped with a VDL4 transponder. A connection between the groundsystem and the airborne system is called a point to point connection, which can be used for various applications. This data link needs to be transferred between groundstations during flights in order maintain the connection, which is called handoff.

    The handoff process needs to be quick enough to not drop the link and at the same time a low rate of handoffs is desirable. The data link is regarded as a narrow resource and link management data for handoff is considered as overhead.

    This thesis studies how to make the handoff procedure optimal with respect to involved aspects. Previous research of handoff algorithms and models of the VHF-channel are treated. Standardized parameters and procedures in VDL4 and are explored in order to find an optimal solution for the handoff procedure in VDL4.

    The studied topics are analyzed and it is concluded to suggest an algorithm based on an adaptive hysteresis including signal quality and positioning data provided in VDL4. Standardized parameters which could be useful in the handoff procedure are commented, since the VDL4 standards are under development.

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  • 25.
    Aronsson, Peter
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Objektdetektering i SAR- och IR-bilder2008Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    This report treats detection in IR-pictures taken from airplanes over the ground. The detection is divided in two parts. First there is a detection with filterkernels with the task to point on targets and objects that look like targets. The second part is a discriminator that demands more calculations and has the task to sort out the false alarms from the discriminator. Both the detector and the discriminator contain thresholds thats been trained from trainingsets of data. The results from the detector was better then expected hence it wasn’t possible to test the diskriminator properly.

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  • 26.
    Aslam, Mohammed Zahid
    et al.
    SIRADEL, France.
    Corre, Yoann
    SIRADEL, France.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Large-scale Massive MIMO Network Evaluation Using Ray-based Deterministic Simulations2018In: 2018 IEEE 29TH ANNUAL INTERNATIONAL SYMPOSIUM ON PERSONAL, INDOOR AND MOBILE RADIO COMMUNICATIONS (PIMRC), IEEE , 2018Conference paper (Refereed)
    Abstract [en]

    Large-scale massive MIMO network deployments can provide higher spectral efficiency and better coverage for future communication systems like 5G. Due to the large number of antennas at the base station, the system achieves stable channel quality and spatially separable channels to the different users. In this paper, linear, planar, circular and cylindrical arrays are used in the evaluation of a large-scale multi-cell massive MIMO network. The system-level performance is predicted using two different kinds of channel models. First, a ray-based deterministic tool is utilized in a real North American city environment. Second, an independent and identically distributed (i.i.d.) Rayleigh fading channel model is considered, as often used in previously published massive MIMO studies. The analysis is conducted in a 16-macro-cell network with outdoor and randomly distributed users. It is shown that the array configuration has a large impact on the throughput statistics. Although the system level performance with i.i.d. Rayleigh fading can be close to the deterministic prediction in some situations (e.g., with large linear arrays), significant differences are noticed when considering other types of arrays.

  • 27.
    Aslam, Mohammed Zahid
    et al.
    SIRADEL, France.
    Corre, Yoann
    SIRADEL, France.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Performance of a dense urban massive MIMO network from a simulated ray-based channel2019In: EURASIP Journal on Wireless Communications and Networking, ISSN 1687-1472, E-ISSN 1687-1499, article id 106Article in journal (Refereed)
    Abstract [en]

    Massive MIMO network deployments are expected to be a key feature of the upcoming 5G communication systems. Such networks are able to achieve a high level of channel quality and can simultaneously serve multiple users with the same resources. In this paper, realistic massive MIMO channels are evaluated both in single and multi-cell environments. The favorable propagation property is evaluated in the single-cell scenario and provides perspectives on the minimal criteria required to achieve such conditions. The dense multi-cell urban scenario provides a comparison between linear, planar, circular, and cylindrical arrays to evaluate a large-scale multi-cell massive MIMO network. The system-level performance is predicted using two different kinds of channel models. First, a ray-based deterministic tool is utilized in a real North American city environment. Second, an independent and identically distributed (i.i.d.) Rayleigh fading channel model is considered, as often used in previously published massive MIMO studies. The analysis is conducted in a 16-macro-cell network with both randomly distributed outdoor and indoor users. It is shown that the physical array properties like the shape and configuration have a large impact on the throughput statistics. Although the system-level performance with i.i.d. Rayleigh fading can be close to the deterministic prediction in some situations (e.g., with large linear arrays), significant differences are noticed when considering other types of arrays. The differences in the performance of the various arrays utilizing the exact same network parameters and the same number of total antenna elements provide insights into the selection of these physical parameters for upcoming 5G networks.

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  • 28.
    Aslam, Mohammed Zahid
    et al.
    Siradel.
    Corre, Yoann
    Siradel.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Lostanlen, Yves
    Siradel.
    Massive MIMO Channel Performance Analysis Considering Separation of Simultaneous Users2018Conference paper (Refereed)
    Abstract [en]

    One of the key aspects of massive MIMO (mMIMO) is its ability to spatially differentiate between multiple simultaneous users. The spatial separability improves as the number of base station (BS) antenna elements is increased. In real BS deployments, the number of BS array elements will be fixed, and expected to provide the required service to a certain number of simultaneous users in the existing propagation environment. The mMIMO performance is investigated in this paper, in an urban macro-cell scenario, using three kinds of channel models with different complexity levels: the independent and identically distributed Rayleigh fading model, a geometry-based stochastic model, and a physical ray-based software. Two performance indicators are analyzed: the favorable propagation metric and the multi-user eigenvalue distribution. Two frequencies (2 GHz and 28 GHz) and two antenna array shapes (linear and circular) are considered and compared.

  • 29.
    Avazkonandeh Gharavol, Ebrahim
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Robust Joint Optimization of MIMO Interfering Relay Channels with Imperfect CSI2011In: 2001 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), Piscataway, NJ, USA: IEEE , 2011, , p. 5p. 209-212Conference paper (Refereed)
    Abstract [en]

    In this paper we deal with the problem of the joint optimization of the precoders, equalizers and relay beamformer of a multiple-input multiple-output interfering relay channel. This network can be regarded az a generalized model for both one-way and two-way relay channels with/without direct interfering links. Unlike the conventional design procedures, we assume that the Channel State Information (CSI) is not known perfectly. The imperfect CSI is described using the norm bounded error framework. We use a system-wide Sum Mean Square Error (SMSE) based problem formulation which is constrained using the transmit power of the terminals and the relay node. The problem at hand, from a worst-case design perspective, is a multilinear, and hence, a nonconvex problem which is also semiinfinite in its constraints. We use a generalized version of the Peterson’s lemma to handle the semi-infiniteness and reduce the original problem to a single Linear Matrix Inequality (LMI). However, this LMI is not convex, and to resolve this issue we propose an iterative algorithm based on the alternating convex search methodology to solve the aforementioned problem. Finally simulation results, i.e., the convergence of the proposed algorithm and the SMSE properties, are included to asses the performance of the proposed algorithm.

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  • 30.
    Avazkonandeh Gharavol, Ebrahim
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Robust Joint Optimization of Non-regenerative MIMO Relay Channels with Imperfect CSI2011In: Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), 2011, IEEE Computer Society, 2011, p. 1589-1593Conference paper (Refereed)
    Abstract [en]

    In this paper, we deal with the problem of joint optimization of the source precoder, the relay beamformer and the destination equalizer in a nonregenerative relay network with only a partial knowledge of the Channel State Information (CSI).

    We model the partial CSI using a deterministic norm bounded error model, and we use a system-wide mean square error performance measure which is constrained based on the transmit power regulations for both source and relay nodes.

    Most conventional designs employ the average performance optimization, however, we solve this problem from a worst-case design perspective.

    The original problem formulation is a semi-infinite trilinear optimization problem which is not convex.

    To solve this problem we extend the existing theories to deal with the constraints which are semi-infinite in different independent complex matrix variables.

    We show that the equivalent approximate problem is a set of linear matrix inequalities, that can be solved iteratively.

    Finally simulation results assess the performance of the proposed scheme.

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  • 31.
    Avazkonandeh Gharavol, Ebrahim
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    The Sign-Definiteness Lemma and Its Applications to Robust Transceiver Optimization for Multiuser MIMO Systems2013In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 61, no 2, p. 238-252Article in journal (Refereed)
    Abstract [en]

    We formally generalize the sign-definiteness lemma to the case of complex-valued matrices and multiple norm-bounded uncertainties. This lemma has found many applications in the study of the stability of control systems, and in the design and optimization of robust transceivers in communications. We then present three different novel applications of this lemma in the area of multi-user multiple-input multiple-output (MIMO) robust transceiver optimization. Specifically, the scenarios of interest are: (i) robust linear beamforming in an interfering adhoc network, (ii) robust design of a general relay network, including the two-way relay channel as a special case, and (iii) a half-duplex one-way relay system with multiple relays. For these networks, we formulate the design problems of minimizing the (sum) MSE of the symbol detection subject to different average power budget constraints. We show that these design problems are non-convex (with bilinear or trilinear constraints) and semiinfinite in multiple independent uncertainty matrix-valued variables. We propose a two-stage solution where in the first step the semi-infinite constraints are converted to linear matrix inequalities using the generalized signdefiniteness lemma, and in the second step, we use an iterative algorithm based on alternating convex search (ACS). Via simulations we evaluate the performance of the proposed scheme.

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  • 32. Order onlineBuy this publication >>
    Axell, Erik
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Spectrum Sensing Algorithms Based on Second-Order Statistics2012Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Cognitive radio is a new concept of reusing spectrum in an opportunistic manner. Cognitive radio is motivated by recent measurements of spectrum utilization, showing unused resources in frequency, time and space. Introducing cognitive radios in a primary network inevitably creates increased interference to the primary users. Secondary users must sense the spectrum and detect primary users' signals at very low SNR, to avoid causing too much interference.This dissertation studies this detection problem, known as spectrum sensing.

    The fundamental problem of spectrum sensing is to discriminate an observation that contains only noise from an observation that contains a very weak signal embedded in noise. In this work, detectors are derived that exploit known properties of the second-order moments of the signal. In particular, known structures of the signal covariance are exploited to circumvent the problem of unknown parameters, such as noise and signal powers or channel coefficients.

    The dissertation is comprised of six papers, all in different ways related to spectrum sensing based on second-order statistics. In the first paper, we considerspectrum sensing of orthogonal frequency-division multiplexed (OFDM) signals in an additive white Gaussian noise channel. For the case of completely known noise and signal powers, we set up a vector-matrix model for an OFDM signal with a cyclic prefix and derive the optimal Neyman-Pearson detector from first principles. For the case of completely unknown noise and signal powers, we derive a generalized likelihood ratio test (GLRT) based on empirical second-order statistics of the received data. The proposed GLRT detector exploits the non-stationary correlation structure of the OFDM signal and does not require any knowledge of the noise or signal powers.

    In the second paper, we create a unified framework for spectrum sensing of signals which have covariance matrices with known eigenvalue multiplicities. We derive the GLRT for this problem, with arbitrary eigenvalue multiplicities under both hypotheses. We also show a number of applications to spectrum sensing for cognitive radio.

    The general result of the second paper is used as a building block, in the third and fourth papers, for spectrum sensing of second-order cyclostationary signals received at multiple antennas and orthogonal space-time block coded (OSTBC) signals respectively. The proposed detector of the third paper exploits both the spatial and the temporal correlation of the received signal, from knowledge of the fundamental period of the cyclostationary signal and the eigenvalue multiplicities of the temporal covariance matrix.

    In the fourth paper, we consider spectrum sensing of signals encoded with an OSTBC. We show how knowledge of the eigenvalue multiplicities of the covariance matrix are inherent owing to the OSTBC, and propose an algorithm that exploits that knowledge for detection. We also derive theoretical bounds on the performance of the proposed detector. In addition, we show that the proposed detector is robust to a carrier frequency offset, and propose another detector that deals with timing synchronization using the detector for the synchronized case as a building block.

    A slightly different approach to covariance matrix estmation is taken in the fifth paper. We consider spectrum sensing of Gaussian signals with structured covariance matrices, and propose to estimate the unknown parameters of the covariance matrices using covariance matching estimation techniques (COMET). We also derive the optimal detector based on a Gaussian approximation of the sample covariance matrix, and show that this is closely connected to COMET.

    The last paper deals with the problem of discriminating samples that containonly noise from samples that contain a signal embedded in noise, when the variance of the noise is unknown. We derive the optimal soft decision detector using a Bayesian approach. The complexity of this optimal detector grows exponentially with the number of observations and as a remedy, we propose a number of approximations to it. The problem under study is a fundamental one andit has applications in signal denoising, anomaly detection, and spectrum sensing for cognitive radio.

    List of papers
    1. Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance
    Open this publication in new window or tab >>Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance
    2011 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 29, no 2, p. 290-304Article in journal (Refereed) Published
    Abstract [en]

    We consider spectrum sensing of OFDM signals in an AWGN channel. For  the case of completely known noise and signal powers, we set up  a vector-matrix model for an OFDM signal with a cyclic prefix and  derive the optimal Neyman-Pearson detector from first  principles. The optimal detector exploits the inherent correlation  of the OFDM signal incurred by the repetition of data in the cyclic  prefix, using knowledge of the length of the cyclic prefix and the  length of the OFDM symbol. We compare the optimal detector to the energy  detector numerically. We show that the energy detector is  near-optimal (within 1 dB SNR) when the noise variance is  known. Thus, when the noise power is known, no substantial gain can  be achieved by using any other detector than the energy detector.

    For the case of completely unknown noise and signal powers, we  derive a generalized likelihood ratio test (GLRT) based onempirical second-order statistics of  the received data. The proposed GLRT detector exploits the  non-stationary correlation structure of the OFDM signal and does not  require any knowledge of the noise power or the signal power. The  GLRT detector is compared to state-of-the-art OFDM signal detectors,  and shown to improve the detection performance with 5 dB SNR in  relevant cases.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2011
    Keywords
    spectrum sensing, signal detection, OFDM, cyclic prefix, subspace detection, second-order statistics
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-58515 (URN)10.1109/JSAC.2011.110203 (DOI)000286676500003 ()
    Note

    ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erik Axell and Erik G. Larsson, Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance, 2011, IEEE Journal on Selected Areas in Communications, (29), 2, 290-304. http://dx.doi.org/10.1109/JSAC.2011.110203

    The previous status of this article was Manuskript.

    Available from: 2010-08-12 Created: 2010-08-12 Last updated: 2017-12-12Bibliographically approved
    2. A Unified Framework for GLRT-Based Spectrum Sensing of Signals with Covariance Matrices with Known Eigenvalue Multiplicities
    Open this publication in new window or tab >>A Unified Framework for GLRT-Based Spectrum Sensing of Signals with Covariance Matrices with Known Eigenvalue Multiplicities
    2011 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speech and SignalProcessing (ICASSP), IEEE conference proceedings, 2011, p. 2956-2959Conference paper, Published paper (Refereed)
    Abstract [en]

    In this paper, we create a unified framework for spectrum sensing of signals which have covariance matrices with known eigenvalue multiplicities. We derive the generalized likelihood-ratio test (GLRT) for this problem, with arbitrary eigenvalue multiplicities under both hypotheses. We also show a number of applications to spectrum sensing for cognitive radio and show that the GLRT for these applications, of which some are already known, are special cases of the general result.

    Place, publisher, year, edition, pages
    IEEE conference proceedings, 2011
    Series
    IEEE International Conference on Acoustics, Speech and SignalProcessing, ISSN 1520-6149
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-64320 (URN)10.1109/ICASSP.2011.5946277 (DOI)000296062403092 ()
    Note
    ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erik Axell and Erik G. Larsson, A Unified Framework for GLRT-Based Spectrum Sensing of Signals with Covariance Matrices with Known Eigenvalue Multiplicities, 2011, Proceedings of the IEEE International Conference on Acoustics, Speech and SignalProcessing (ICASSP), 2956-2959. http://dx.doi.org/10.1109/ICASSP.2011.5946277 Available from: 2011-01-19 Created: 2011-01-19 Last updated: 2016-08-31
    3. Multiantenna Spectrum Sensing of a Second-Order Cyclostationary Signal
    Open this publication in new window or tab >>Multiantenna Spectrum Sensing of a Second-Order Cyclostationary Signal
    2011 (English)In: Proceedings of the 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP'11), 2011, p. 329-332Conference paper, Published paper (Refereed)
    Abstract [en]

    We consider spectrum sensing of a second-order cyclostationary signal receivedat multiple antennas. The proposed detector exploits both the spatial andthe temporal correlation of the received signal, from knowledge of thefundamental period of the cyclostationary signal and the eigenvaluemultiplicities of the temporal covariance matrix. All other parameters, suchas the channel gains or the noise power, are assumed to be unknown. The proposeddetector is shown numerically to outperform state-of-the-art detectors forspectrum sensing of anOFDM signal, both when using a single antenna and with multiple antennas.

    Keywords
    spectrum sensing, multiple antennas, cyclostationarity, GLRT
    National Category
    Communication Systems Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-70858 (URN)10.1109/CAMSAP.2011.6136017 (DOI)978-1-4577-2103-8 (ISBN)
    Conference
    4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), December 13-16 2011, San Juan, Puerto Rico (USA)
    Funder
    eLLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Research Council
    Available from: 2011-09-20 Created: 2011-09-20 Last updated: 2016-08-31Bibliographically approved
    4. Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas
    Open this publication in new window or tab >>Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas
    2010 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2010, p. 3110-3113Conference paper, Published paper (Other academic)
    Abstract [en]

    We consider detection of signals encoded with orthogonal space-time block codes (OSTBC), using multiple receive antennas. Such signals contain redundancy and they have a specific structure, that can be exploited for detection. We derive the optimal detector, in the Neyman-Pearson sense, when all parameters are known. We also consider unknown noise variance, signal variance and channel coefficients. We propose a number of GLRT based detectors for the different cases, that exploit the redundancy structure of the OSTBC signal. We also propose an eigenvalue-based detector for the case when all parameters are unknown. The proposed detectors are compared to the energy detector. We show that when only the noise variance is known, there is no gain in exploiting the structure of the OSTBC. However, when the noise variance is unknown there can be a significant gain.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2010
    Series
    Acoustics Speech and Signal Processing (ICASSP), ISSN 1520-6149, E-ISSN 2379-190X
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-51745 (URN)10.1109/ICASSP.2010.5496088 (DOI)000287096003014 ()9781424442959 (ISBN)9781424442966 (ISBN)
    Conference
    IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010, 14-19 March, Dallas, Texas, U.S.A.
    Note

    ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.: Erik Axell and Erik G. Larsson, Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas, 2010, Proceedings of the 35th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'10).

    The previous status of this articel was Manuscript.

    Available from: 2009-11-17 Created: 2009-11-17 Last updated: 2018-02-02Bibliographically approved
    5. Spectrum Sensing of Signals with Structured Covariance Matrices Using Covariance Matching Estimation Techniques
    Open this publication in new window or tab >>Spectrum Sensing of Signals with Structured Covariance Matrices Using Covariance Matching Estimation Techniques
    2011 (English)In: Proceedings of the IEEE Global Communications Conference (GLOBECOM), 2011, p. 1-5Conference paper, Published paper (Refereed)
    Abstract [en]

    In this work, we consider spectrum sensing of Gaussian signals with structured covariance matrices. We show that the optimal detector based on the probability distribution of the sample covariance matrix is equivalent to the optimal detector based on the raw data, if the covariance matrices are known. However, the covariance matrices are unknown in general. Therefore, we propose to estimate the unknown parameters using covariance matching estimation techniques (COMET). We also derive the optimal detector based on a Gaussian approximation of the sample covariance matrix, and show that this is closely connected to COMET.

    Keywords
    spectrum sensing, sample covariance, COMET
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-69639 (URN)10.1109/GLOCOM.2011.6133506 (DOI)978-1-4244-9267-1 (ISBN)978-1-4244-9266-4 (ISBN)
    Conference
    IEEE Global Communications Conference (GLOBECOM), 3-7 December, Anaheim, California, USA
    Available from: 2011-07-08 Created: 2011-07-08 Last updated: 2016-08-31
    6. A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection
    Open this publication in new window or tab >>A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection
    2009 (English)In: Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 2009, p. 2333-2336Conference paper, Published paper (Refereed)
    Abstract [en]

    This paper deals with the problem of discriminating samples that contain only noise from samples that contain a signal embedded in noise. The focus is on the case when the variance of the noise is unknown. We derive the optimal soft decision detector using a Bayesian approach. The complexity of this optimal detector grows exponentially with the number of observations and as a remedy, we propose a number of approximations to it. The problem under study is a fundamental one and it has applications in signal denoising, anomaly detection, and spectrum sensing for cognitive radio. We illustrate the results in the context of the latter.

    Series
    Acoustics, Speech and Signal Processing, ISSN 1520-6149 ; 2009
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-25592 (URN)10.1109/ICASSP.2009.4960088 (DOI)978-1-4244-2354-5 (ISBN)978-1-4244-2353-8 (ISBN)
    Conference
    34th IEEE international conference on acoustics, speech and signal processing,19-24 April, Taipei, Taiwan
    Note
    ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erik Axell and Erik G. Larsson, A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection, 2009, Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 2333-2336. http://dx.doi.org/10.1109/ICASSP.2009.4960088Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2016-08-31Bibliographically approved
    Download full text (pdf)
    Spectrum Sensing Algorithms Based on Second-Order Statistics
    Download (pdf)
    omslag
  • 33. Order onlineBuy this publication >>
    Axell, Erik
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Topics in Spectrum Sensing for Cognitive Radio2009Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    Cognitive radio is a new concept of reusing licensed spectrum in an unlicensed manner. Cognitive radio is motivated by recent measurements of spectrum utilization, showing unused resources in frequency, time and space. The spectrum must be sensed to detect primary user signals, in order to allow cognitive radios in a primary system. In this thesis we study some topics in spectrum sensing for cognitive radio.

    The fundamental problem of spectrum sensing is to discriminate samples that contain only noise from samples that contain a very weak signal embedded in noise. We derive detectors that exploit known structures of the signal, for the cases of an OFDM modulated signal and an orthogonal space-time block coded signal. We derive optimal detectors, in the Neyman-Pearson sense, for a few different cases when all parameters are known. Moreover we study detection when the parameters, such as noise variance, are unknown. We propose solutions the problem of unknown parameters.

    We also study system aspects of cognitive radio. More specifically, we investigate spectrum reuse of geographical spectrum holes in a frequency planned primary network. System performance is measured in terms of the achievable rate for the cognitive radio system. Simulation results show that a substantial sum-rate could be achieved if the cognitive radios communicate over small distances. However, the spectrum hole gets saturated quite fast, due to interference caused by the cognitive radios.

    List of papers
    1. A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection
    Open this publication in new window or tab >>A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection
    2009 (English)In: Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 2009, p. 2333-2336Conference paper, Published paper (Refereed)
    Abstract [en]

    This paper deals with the problem of discriminating samples that contain only noise from samples that contain a signal embedded in noise. The focus is on the case when the variance of the noise is unknown. We derive the optimal soft decision detector using a Bayesian approach. The complexity of this optimal detector grows exponentially with the number of observations and as a remedy, we propose a number of approximations to it. The problem under study is a fundamental one and it has applications in signal denoising, anomaly detection, and spectrum sensing for cognitive radio. We illustrate the results in the context of the latter.

    Series
    Acoustics, Speech and Signal Processing, ISSN 1520-6149 ; 2009
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-25592 (URN)10.1109/ICASSP.2009.4960088 (DOI)978-1-4244-2354-5 (ISBN)978-1-4244-2353-8 (ISBN)
    Conference
    34th IEEE international conference on acoustics, speech and signal processing,19-24 April, Taipei, Taiwan
    Note
    ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erik Axell and Erik G. Larsson, A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection, 2009, Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 2333-2336. http://dx.doi.org/10.1109/ICASSP.2009.4960088Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2016-08-31Bibliographically approved
    2. On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate
    Open this publication in new window or tab >>On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate
    2009 (English)In: Proceedings of the 2009 IEEE Workshop on Statistical Signal Processing (SSP'09), IEEE , 2009, p. 245-248Conference paper, Published paper (Refereed)
    Abstract [en]

    This paper considers approximations of marginalization sums thatarise in Bayesian inference problems. Optimal approximations ofsuch marginalization sums, using a fixed number of terms, are analyzedfor a simple model. The model under study is motivated byrecent studies of linear regression problems with sparse parametervectors, and of the problem of discriminating signal-plus-noise samplesfrom noise-only samples. It is shown that for the model understudy, if only one term is retained in the marginalization sum, thenthis term should be the one with the largest a posteriori probability.By contrast, if more than one (but not all) terms are to be retained,then these should generally not be the ones corresponding tothe components with largest a posteriori probabilities.

    Place, publisher, year, edition, pages
    IEEE, 2009
    Keywords
    MMSE estimation, Bayesian inference, marginalization
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-25591 (URN)10.1109/SSP.2009.5278594 (DOI)000274988800062 ()978-1-4244-2709-3 (ISBN)
    Note
    ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erik Axell, Erik G. Larsson and Jan-Åke Larsson, On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate, 2009, Proceedings of the 2009 IEEE Workshop on Statistical Signal Processing (SSP'09), 245-248. http://dx.doi.org/10.1109/SSP.2009.5278594 Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2016-08-31Bibliographically approved
    3. Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance
    Open this publication in new window or tab >>Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance
    2011 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 29, no 2, p. 290-304Article in journal (Refereed) Published
    Abstract [en]

    We consider spectrum sensing of OFDM signals in an AWGN channel. For  the case of completely known noise and signal powers, we set up  a vector-matrix model for an OFDM signal with a cyclic prefix and  derive the optimal Neyman-Pearson detector from first  principles. The optimal detector exploits the inherent correlation  of the OFDM signal incurred by the repetition of data in the cyclic  prefix, using knowledge of the length of the cyclic prefix and the  length of the OFDM symbol. We compare the optimal detector to the energy  detector numerically. We show that the energy detector is  near-optimal (within 1 dB SNR) when the noise variance is  known. Thus, when the noise power is known, no substantial gain can  be achieved by using any other detector than the energy detector.

    For the case of completely unknown noise and signal powers, we  derive a generalized likelihood ratio test (GLRT) based onempirical second-order statistics of  the received data. The proposed GLRT detector exploits the  non-stationary correlation structure of the OFDM signal and does not  require any knowledge of the noise power or the signal power. The  GLRT detector is compared to state-of-the-art OFDM signal detectors,  and shown to improve the detection performance with 5 dB SNR in  relevant cases.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2011
    Keywords
    spectrum sensing, signal detection, OFDM, cyclic prefix, subspace detection, second-order statistics
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-58515 (URN)10.1109/JSAC.2011.110203 (DOI)000286676500003 ()
    Note

    ©2011 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Erik Axell and Erik G. Larsson, Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance, 2011, IEEE Journal on Selected Areas in Communications, (29), 2, 290-304. http://dx.doi.org/10.1109/JSAC.2011.110203

    The previous status of this article was Manuskript.

    Available from: 2010-08-12 Created: 2010-08-12 Last updated: 2017-12-12Bibliographically approved
    4. Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas
    Open this publication in new window or tab >>Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas
    2010 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2010, p. 3110-3113Conference paper, Published paper (Other academic)
    Abstract [en]

    We consider detection of signals encoded with orthogonal space-time block codes (OSTBC), using multiple receive antennas. Such signals contain redundancy and they have a specific structure, that can be exploited for detection. We derive the optimal detector, in the Neyman-Pearson sense, when all parameters are known. We also consider unknown noise variance, signal variance and channel coefficients. We propose a number of GLRT based detectors for the different cases, that exploit the redundancy structure of the OSTBC signal. We also propose an eigenvalue-based detector for the case when all parameters are unknown. The proposed detectors are compared to the energy detector. We show that when only the noise variance is known, there is no gain in exploiting the structure of the OSTBC. However, when the noise variance is unknown there can be a significant gain.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2010
    Series
    Acoustics Speech and Signal Processing (ICASSP), ISSN 1520-6149, E-ISSN 2379-190X
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-51745 (URN)10.1109/ICASSP.2010.5496088 (DOI)000287096003014 ()9781424442959 (ISBN)9781424442966 (ISBN)
    Conference
    IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2010, 14-19 March, Dallas, Texas, U.S.A.
    Note

    ©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.: Erik Axell and Erik G. Larsson, Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas, 2010, Proceedings of the 35th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'10).

    The previous status of this articel was Manuscript.

    Available from: 2009-11-17 Created: 2009-11-17 Last updated: 2018-02-02Bibliographically approved
    5. Capacity Considerations for Uncoordinated Communication in Geographical Spectrum Holes
    Open this publication in new window or tab >>Capacity Considerations for Uncoordinated Communication in Geographical Spectrum Holes
    2009 (English)In: Physical Communication, ISSN 1874-4907, Vol. 2, no 1-2, p. 3-9Article in journal (Refereed) Published
    Abstract [en]

    Cognitive radio is a new concept of reusing a licensed spectrum in an unlicensed manner. The motivation for cognitive radio is various measurements of spectrum utilization, that generally show unused resources in frequency, time and space. These "spectrum holes" could be exploited by cognitive radios. Some studies suggest that the spectrum is extremely underutilized, and that these spectrum holes could provide ten times the capacity of all existing wireless devices together. The spectrum could be reused either during time periods where the primary system is not active, or in geographical positions where the primary system is not operating. In this paper, we deal primarily with the concept of geographical reuse, in a frequency-planned primary network. We perform an analysis of the potential for communication in a geographical spectrum hole, and in particular the achievable sum-rate for a secondary network, to some order of magnitude. Simulation results show that a substantial sum-rate could be achieved if the secondary users communicate over small distances. For a small number of secondary links, the sum-rate increases linearly with the number of links. However, the spectrum hole gets saturated quite fast, due to interference caused by the secondary users. A spectrum hole may look large, but it disappears as soon as someone starts using it.

    Place, publisher, year, edition, pages
    Elsevier, 2009
    Keywords
    achievable rate, capacity, cognitive radio, spectrum hole
    National Category
    Engineering and Technology
    Identifiers
    urn:nbn:se:liu:diva-21547 (URN)10.1016/j.phycom.2009.03.002 (DOI)
    Note
    Original Publication: Erik Axell, Erik G. Larsson and Danyo Danev, Capacity Considerations for Uncoordinated Communication in Geographical Spectrum Holes, 2009, Physical Communication, (2), 1-2, 3-9. http://dx.doi.org/10.1016/j.phycom.2009.03.002 Copyright: Elsevier Science B.V., Amsterdam http://www.elsevier.com/ Available from: 2009-10-03 Created: 2009-10-02 Last updated: 2016-08-31Bibliographically approved
    Download full text (pdf)
    Topics in Spectrum Sensing for Cognitive Radio
    Download (pdf)
    Cover
  • 34.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    A Bayesian Approach to Spectrum Sensing, Denoising and Anomaly Detection2009In: Proceedings of the 34th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP'09), 2009, p. 2333-2336Conference paper (Refereed)
    Abstract [en]

    This paper deals with the problem of discriminating samples that contain only noise from samples that contain a signal embedded in noise. The focus is on the case when the variance of the noise is unknown. We derive the optimal soft decision detector using a Bayesian approach. The complexity of this optimal detector grows exponentially with the number of observations and as a remedy, we propose a number of approximations to it. The problem under study is a fundamental one and it has applications in signal denoising, anomaly detection, and spectrum sensing for cognitive radio. We illustrate the results in the context of the latter.

    Download full text (pdf)
    FULLTEXT01
  • 35.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    A Unified Framework for GLRT-Based Spectrum Sensing of Signals with Covariance Matrices with Known Eigenvalue Multiplicities2011In: Proceedings of the IEEE International Conference on Acoustics, Speech and SignalProcessing (ICASSP), IEEE conference proceedings, 2011, p. 2956-2959Conference paper (Refereed)
    Abstract [en]

    In this paper, we create a unified framework for spectrum sensing of signals which have covariance matrices with known eigenvalue multiplicities. We derive the generalized likelihood-ratio test (GLRT) for this problem, with arbitrary eigenvalue multiplicities under both hypotheses. We also show a number of applications to spectrum sensing for cognitive radio and show that the GLRT for these applications, of which some are already known, are special cases of the general result.

    Download full text (pdf)
    fulltext
  • 36.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Comments on "Multiple Antenna Spectrum Sensing in Cognitive Radios"2011In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 10, no 5, p. 1678-1680Article in journal (Refereed)
    Abstract [en]

    We point out an error in a derivation in the recent paper [1], and provide a correct and much shorter calculation of the result in question. In passing, we also connect the results in [1] to the literature on array signal processing and on principal component analysis, and show that the main findings of [1] follow as special cases of standard results in these fields.

    Download full text (pdf)
    fulltext
  • 37.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Eigenvalue-Based Spectrum Sensing of Orthogonal Space-Time Block Coded Signals2012In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 60, no 12, p. 6724-6728Article in journal (Refereed)
    Abstract [en]

    We consider spectrum sensing of signals encoded with an orthogonal space-time block code (OSTBC). We propose a CFAR detector based on knowledge of the eigenvalue multiplicities of the covariance matrix which are inherent owing to the OSTBC and derive theoretical performance bounds. In addition, we show that the proposed detector is robust to a carrier frequency offset, and propose a detector that deals with timing synchronization using the detector for the synchronized case as a building block. The proposed detectors are shown numerically to perform well.

  • 38.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Multiantenna Spectrum Sensing of a Second-Order Cyclostationary Signal2011In: Proceedings of the 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP'11), 2011, p. 329-332Conference paper (Refereed)
    Abstract [en]

    We consider spectrum sensing of a second-order cyclostationary signal receivedat multiple antennas. The proposed detector exploits both the spatial andthe temporal correlation of the received signal, from knowledge of thefundamental period of the cyclostationary signal and the eigenvaluemultiplicities of the temporal covariance matrix. All other parameters, suchas the channel gains or the noise power, are assumed to be unknown. The proposeddetector is shown numerically to outperform state-of-the-art detectors forspectrum sensing of anOFDM signal, both when using a single antenna and with multiple antennas.

  • 39.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Optimal and Near-Optimal Spectrum Sensing of OFDM Signals in AWGN Channels2010In: Proceedings of the International Workshop on Cognitive Information Processing (CIP), 2010Conference paper (Refereed)
    Abstract [en]

    We consider spectrum sensing of OFDM signals in an AWGN channel. For the case of completely unknown noise and signal powers, we  derive a GLRT detector based on empirical second-order statistics of  the received data. The proposed GLRT detector exploits the  non-stationary correlation structure of the OFDM signal and does not  require any knowledge of the noise power or the signal power. The  GLRT detector is compared to state-of-the-art OFDM signal detectors,  and shown to improve the detection performance with 5 dB SNR in  relevant cases.

    For the case of completely known noise power and signal power, we present a brief  derivation of the optimal Neyman-Pearson detector from first  principles. We compare the optimal detector to the energy  detector numerically, and show that the energy detector is  near-optimal (within 0.2 dB SNR) when the noise variance is  known. Thus, when the noise power is known, no substantial gain can  be achieved by using any other detector than the energy detector.

    Download full text (pdf)
    FULLTEXT01
  • 40.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Optimal and Sub-Optimal Spectrum Sensing of OFDM Signals in Known and Unknown Noise Variance2011In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 29, no 2, p. 290-304Article in journal (Refereed)
    Abstract [en]

    We consider spectrum sensing of OFDM signals in an AWGN channel. For  the case of completely known noise and signal powers, we set up  a vector-matrix model for an OFDM signal with a cyclic prefix and  derive the optimal Neyman-Pearson detector from first  principles. The optimal detector exploits the inherent correlation  of the OFDM signal incurred by the repetition of data in the cyclic  prefix, using knowledge of the length of the cyclic prefix and the  length of the OFDM symbol. We compare the optimal detector to the energy  detector numerically. We show that the energy detector is  near-optimal (within 1 dB SNR) when the noise variance is  known. Thus, when the noise power is known, no substantial gain can  be achieved by using any other detector than the energy detector.

    For the case of completely unknown noise and signal powers, we  derive a generalized likelihood ratio test (GLRT) based onempirical second-order statistics of  the received data. The proposed GLRT detector exploits the  non-stationary correlation structure of the OFDM signal and does not  require any knowledge of the noise power or the signal power. The  GLRT detector is compared to state-of-the-art OFDM signal detectors,  and shown to improve the detection performance with 5 dB SNR in  relevant cases.

    Download full text (pdf)
    FULLTEXT02
  • 41.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Spectrum Sensing of Orthogonal Space-Time Block Coded Signals with Multiple Receive Antennas2010In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Institute of Electrical and Electronics Engineers (IEEE), 2010, p. 3110-3113Conference paper (Other academic)
    Abstract [en]

    We consider detection of signals encoded with orthogonal space-time block codes (OSTBC), using multiple receive antennas. Such signals contain redundancy and they have a specific structure, that can be exploited for detection. We derive the optimal detector, in the Neyman-Pearson sense, when all parameters are known. We also consider unknown noise variance, signal variance and channel coefficients. We propose a number of GLRT based detectors for the different cases, that exploit the redundancy structure of the OSTBC signal. We also propose an eigenvalue-based detector for the case when all parameters are unknown. The proposed detectors are compared to the energy detector. We show that when only the noise variance is known, there is no gain in exploiting the structure of the OSTBC. However, when the noise variance is unknown there can be a significant gain.

    Download full text (pdf)
    FULLTEXT01
  • 42.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Spectrum Sensing of Signals with Structured Covariance Matrices Using Covariance Matching Estimation Techniques2011In: Proceedings of the IEEE Global Communications Conference (GLOBECOM), 2011, p. 1-5Conference paper (Refereed)
    Abstract [en]

    In this work, we consider spectrum sensing of Gaussian signals with structured covariance matrices. We show that the optimal detector based on the probability distribution of the sample covariance matrix is equivalent to the optimal detector based on the raw data, if the covariance matrices are known. However, the covariance matrices are unknown in general. Therefore, we propose to estimate the unknown parameters using covariance matching estimation techniques (COMET). We also derive the optimal detector based on a Gaussian approximation of the sample covariance matrix, and show that this is closely connected to COMET.

  • 43.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Danev, Danyo
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Capacity Considerations for Uncoordinated Communication in Geographical Spectrum Holes2009In: Physical Communication, ISSN 1874-4907, Vol. 2, no 1-2, p. 3-9Article in journal (Refereed)
    Abstract [en]

    Cognitive radio is a new concept of reusing a licensed spectrum in an unlicensed manner. The motivation for cognitive radio is various measurements of spectrum utilization, that generally show unused resources in frequency, time and space. These "spectrum holes" could be exploited by cognitive radios. Some studies suggest that the spectrum is extremely underutilized, and that these spectrum holes could provide ten times the capacity of all existing wireless devices together. The spectrum could be reused either during time periods where the primary system is not active, or in geographical positions where the primary system is not operating. In this paper, we deal primarily with the concept of geographical reuse, in a frequency-planned primary network. We perform an analysis of the potential for communication in a geographical spectrum hole, and in particular the achievable sum-rate for a secondary network, to some order of magnitude. Simulation results show that a substantial sum-rate could be achieved if the secondary users communicate over small distances. For a small number of secondary links, the sum-rate increases linearly with the number of links. However, the spectrum hole gets saturated quite fast, due to interference caused by the secondary users. A spectrum hole may look large, but it disappears as soon as someone starts using it.

    Download full text (pdf)
    FULLTEXT01
  • 44.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Larsson, Jan-Åke
    Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, The Institute of Technology.
    On the Optimal K-term Approximation of a Sparse Parameter Vector MMSE Estimate2009In: Proceedings of the 2009 IEEE Workshop on Statistical Signal Processing (SSP'09), IEEE , 2009, p. 245-248Conference paper (Refereed)
    Abstract [en]

    This paper considers approximations of marginalization sums thatarise in Bayesian inference problems. Optimal approximations ofsuch marginalization sums, using a fixed number of terms, are analyzedfor a simple model. The model under study is motivated byrecent studies of linear regression problems with sparse parametervectors, and of the problem of discriminating signal-plus-noise samplesfrom noise-only samples. It is shown that for the model understudy, if only one term is retained in the marginalization sum, thenthis term should be the one with the largest a posteriori probability.By contrast, if more than one (but not all) terms are to be retained,then these should generally not be the ones corresponding tothe components with largest a posteriori probabilities.

    Download full text (pdf)
    FULLTEXT01
  • 45.
    Axell, Erik
    et al.
    Dept. of Robust Telecommunications, Swedish Defence Research Agency, Sweden .
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Persson, Daniel
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    GNSS spoofing detection using multiple mobile COTS receivers2015In: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 3192-3196Conference paper (Refereed)
    Abstract [en]

    In this paper we deal with spoofing detection in GNSS receivers. We derive the optimal genie detector when the true positions are perfectly known, and the observation errors are Gaussian, as a benchmark for other detectors. The system model considers three dimensional positions, and includes correlated errors. In addition, we propose several detectors that do not need any position knowledge, that outperform recently proposed detectors in many interesting cases.

  • 46.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Leus, Geert
    Delft University of Technology.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Overview of Spectrum Sensing for Cognitive Radio2010In: Proceedings of the International Workshop on Cognitive Information Processing (CIP), 2010, p. 322-327Conference paper (Refereed)
    Abstract [en]

    We present a survey of state-of-the-art algorithms for spectrum  sensing in cognitive radio. The algorithms discussed range from  energy detection to sophisticated feature detectors. The feature  detectors that we present all have in common that they exploit some  known structure of the transmitted signal.  In particular we treat  detectors that exploit cyclostationarity properties of the signal,  and detectors that exploit a known eigenvalue structure of the  signal covariance matrix.  We also consider cooperative  detection. Specifically we present data fusion rules for soft and  hard combining, and discuss the energy efficiency of several  different sensing, sleeping and censoring schemes in detail.

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    FULLTEXT01
  • 47.
    Axell, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Leus, Geert
    Delft University of Technology, Faculty of Electrical Engineering, Mathematics and Computer Science.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Poor, H. Vincent
    Princeton University, Department of Electrical Engineering.
    Spectrum sensing for cognitive radio: State-of-the-art and recent advances2012In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 29, no 3, p. 101-116Article in journal (Refereed)
    Abstract [en]

    The ever-increasing demand for higher data rates in wireless communications in the face of limited or underutilized spectral resources has motivated the introduction of cognitive radio. Traditionally, licensed spectrum is allocated over relatively long time periods and is intended to be used only by licensees. Various measurements of spectrum utilization have shown substantial unused resources in frequency, time, and space [1], [2]. The concept behind cognitive radio is to exploit these underutilized spectral resources by reusing unused spectrum in an opportunistic manner [3], [4]. The phrase cognitive radio is usually attributed to Mitola [4], but the idea of using learning and sensing machines to probe the radio spectrum was envisioned several decades earlier (cf., [5]).

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    fulltext
  • 48.
    Ayanoglu, Ender
    et al.
    University of California, Irvine.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Karipidis, Eleftherios
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Computational Complexity of Decoding Orthogonal Space-Time Block Codes2010In: Proceedings of the IEEE International Conference on Communications (ICC), 2010, p. 1-6Conference paper (Refereed)
    Abstract [en]

    The computational complexity of optimum decoding for an orthogonal space-time block code is quantified. Four equivalent techniques of optimum decoding which have the same computational complexity are specified. Modifications to the basic formulation in special cases are calculated and illustrated by means of examples.

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    FULLTEXT01
  • 49. Ayanoglu, Ender
    et al.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Karipidis, Eleftherios
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Computational Complexity of Decoding Orthogonal Space-Time Block Codes2011In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 59, no 4, p. 936-941Article in journal (Refereed)
    Abstract [en]

    The computational complexity of optimum decoding for an orthogonal space-time block code {cal G}_N satisfying {cal G}_N^H{cal G}_N=c(∑_{k=1}^Kos_ko^2)I_N where c is a positive integer is quantified. Four equivalent techniques of optimum decoding which have the same computational complexity are specified. Modifications to the basic formulation in special cases are calculated and illustrated by means of examples. This paper corrects and extends and unifies them with the results from the literature. In addition, a number of results from the literature are extended to the case c>1.

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    FULLTEXT01
  • 50.
    Azhar, Rizwan
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Upgrading and Performance Analysis of Thin Clients in Server Based Scientific Computing2011Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Server Based Computing (SBC) technology allows applications to be deployed, managed, supported and executed on the server and not on the client; only the screen information is transmitted between the server and client. This architecture solves many fundamental problems with application deployment, technical support, data storage, hardware and software upgrades.

    This thesis is targeted at upgrading and evaluating performance of thin clients in scientific Server Based Computing (SBC). Performance of Linux based SBC was assessed via methods of both quantitative and qualitative research. Quantitative method used benchmarks that measured typical-load performance with SAR and graphics performance with X11perf, Xbench and SPECviewperf. Structured interview, a qualitative research method, was adopted in which the number of open-ended questions in specific order was presented to users in order to estimate user-perceived performance.

    The first performance bottleneck identified was the CPU speed. The second performance bottleneck, with respect to graphics intensive applications, includes the network latency of the X11 protocol and the subsequent performance of old thin clients. An upgrade of both the computational server and thin clients was suggested.

    The evaluation after the upgrade involved performance analysis via quantitative and qualitative methods. The results showed that the new configuration had improved the performance.

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    Upgrading and Performance Analysis of Thin Clients in Server Based Scientific Computing
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