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  • 51.
    Bertilsson, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Oscar
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    A Modular Base Station Architecture for Massive MIMO with Antenna and User Scalability per Processing Node2018In: 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, IEEE , 2018, p. 1649-1653Conference paper (Refereed)
    Abstract [en]

    Massive MIMO is key technology for the upcoming fifth generation cellular networks (5G), promising high spectral efficiency, low power consumption, and the use of cheap hardware to reduce costs. Previous work has shown how to create a distributed processing architecture, where each node in a network performs the computations related to one or more antennas. The required total number of antennas, M, at the base station depends on the number of simultaneously operating terminals, K. In this work, a flexible node architecture is presented, where the number of terminals can he traded for additional antennas at the same node. This means that the same node can be used with a wide range of system configurations. The computational complexity, along with the order in which to compute incoming and outgoing symbols is explored.

  • 52.
    Bertilsson, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Oscar
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    A Scalable Architecture for Massive MIMO Base Stations Using Distributed Processing2016In: 2016 50TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, Washington: IEEE COMPUTER SOC , 2016, p. 864-868Conference paper (Refereed)
    Abstract [en]

    Massive MIMO-systems have received considerable attention in recent years as an enabler in future wireless communication systems. As the idea is based on having a large number of antennas at the base station it is important to have both a scalable and distributed realization of such a system to ease deployment. Most work so far have focused on the theoretical aspects although a few demonstrators have been reported. In this work, we propose a base station architecture based on connecting the processing nodes in a K-ary tree, allowing simple scalability. Furthermore, it is shown that most of the processing can be performed locally in each node. Further analysis of the node processing shows that it should be enough that each node contains one or two complex multipliers and a few complex adders/subtracters operating at some hundred MHz. It is also shown that a communication link of some Gbps is required between the nodes, and, hence, it is fully feasible to have one or a few links between the nodes to cope with the communication requirements.

  • 53.
    Bertilsson, Erik
    et al.
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Gustafsson, Oscar
    Linköping University, Department of Electrical Engineering, Computer Engineering. Linköping University, Faculty of Science & Engineering.
    Larsson, Erik G.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Computation Limited Matrix Inversion Using Neumann Series Expansion for Massive MIMO2017In: 2017 FIFTY-FIRST ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, 2017, p. 466-469Conference paper (Refereed)
    Abstract [en]

    Neumann series expansion is a method for performing matrix inversion that has received a lot of interest in the context of massive MIMO systems. However, the computational complexity of the Neumann methods is higher than for the lowest complexity exact matrix inversion algorithms, such as LDL, when the number of terms in the series is three or more. In this paper, the Neumann series expansion is analyzed from a computational perspective for cases when the complexity of performing exact matrix inversion is too high. By partially computing the third term of the Neumann series, the computational complexity can be reduced. Three different preconditioning matrices are considered. Simulation results show that when limiting the total number of operations performed, the BER performance of the tree different preconditioning matrices is the same.

  • 54.
    Biswas, Kamal
    et al.
    IITD, India.
    Mohammed, Saif Khan
    IITD, India.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Efficient Techniques for Broadcast of System Information in mmWave Communication Systems2018In: 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2018, p. 366-370Conference paper (Refereed)
    Abstract [en]

    In this paper we consider Millimeter wave (mmWave) Massive MIMO systems where a large antenna array at the base station (BS) serves a few scheduled terminals. The high dimensional null space of the channel matrix to the scheduled terminals is utilized to broadcast system information to the non-scheduled terminals on the same time-frequency resource. Our analysis reveals the interesting result that with a sufficiently large antenna array this non-orthogonal broadcast strategy requires significantly less total transmit power when compared to the traditional orthogonal strategy where a fraction of the total resource is reserved for broadcast of system information.

  • 55.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Reproducible Research: Best Practices and Potential Misuse2019In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 36, no 3, p. 106-+Article in journal (Other academic)
    Abstract [en]

    n/a

  • 56.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Bengtsson, Mats
    KTH Royal Institute of Technology, Stockholm, Sweden .
    Ottersten, Björn
    KTH Royal Institute of Technology, Stockholm, Sweden; University of Luxembourg.
    Optimal Multiuser Transmit Beamforming: A Difficult Problem with a Simple Solution Structure2014In: IEEE signal processing magazine (Print), ISSN 1053-5888, E-ISSN 1558-0792, Vol. 31, no 4, p. 142-148Article in journal (Refereed)
    Abstract [en]

    Transmit beamforming is a versatile technique for signal transmission from an array of antennas to one or multiple users [1]. In wireless communications, the goal is to increase the signal power at the intended user and reduce interference to nonintended users. A high signal power is achieved by transmitting the same data signal from all antennas but with different amplitudes and phases, such that the signal components add coherently at the user. Low interference is accomplished by making the signal components add destructively at nonintended users. This corresponds mathematically to designing beamforming vectors (that describe the amplitudes and phases) to have large inner products with the vectors describing the intended channels and small inner products with nonintended user channels.

  • 57.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    de Carvalho, Elisabeth
    Aalborg University, Denmark.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Popovski, Petar
    Aalborg University, Denmark.
    Random Access Protocol for Massive MIMO: Strongest-User Collision Resolution (SUCR)2016In: 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE , 2016, p. 820-825Conference paper (Refereed)
    Abstract [en]

    Wireless networks with many antennas at the base stations and multiplexing of many users, known as Massive MIMO systems, are key to handle the rapid growth of data traffic. As the number of users increases, the random access in contemporary networks will be flooded by user collisions. In this paper, we propose a reengineered random access protocol, coined strongest-user collision resolution (SUCR). It exploits the channel hardening feature of Massive MIMO channels to enable each user to detect collisions, determine how strong the contenders channels are, and only keep transmitting if it has the strongest channel gain. The proposed SUCR protocol can quickly and distributively resolve the vast majority of all pilot collisions.

  • 58.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    de Carvalho, Elisabeth
    Aalborg University, Denmark.
    Sorensen, Jesper H.
    Aalborg University, Denmark.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Popovski, Petar
    Aalborg University, Denmark.
    A Random Access Protocol for Pilot Allocation in Crowded Massive MIMO Systems2017In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 16, no 4, p. 2220-2234Article in journal (Refereed)
    Abstract [en]

    The massive multiple-input multiple-output (MIMO) technology has great potential to manage the rapid growth of wireless data traffic. Massive MIMO achieves tremendous spectral efficiency by spatial multiplexing many tens of user equipments (UEs). These gains are only achieved in practice if many more UEs can connect efficiently to the network than today. As the number of UEs increases, while each UE intermittently accesses the network, the random access functionality becomes essential to share the limited number of pilots among the UEs. In this paper, we revisit the random access problem in the Massive MIMO context and develop a reengineered protocol, termed strongest-user collision resolution (SUCRe). An accessing UE asks for a dedicated pilot by sending an uncoordinated random access pilot, with a risk that other UEs send the same pilot. The favorable propagation of massive MIMO channels is utilized to enable distributed collision detection at each UE, thereby determining the strength of the contenders signals and deciding to repeat the pilot if the UE judges that its signal at the receiver is the strongest. The SUCRe protocol resolves the vast majority of all pilot collisions in crowded urban scenarios and continues to admit UEs efficiently in overloaded networks.

  • 59.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Hoydis, Jakob
    Paris Saclay, France.
    Sanguinetti, Luca
    Univ Pisa, Italy.
    Massive MIMO Has Unlimited Capacity2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 1, p. 574-590Article in journal (Refereed)
    Abstract [en]

    The capacity of cellular networks can be improved by the unprecedented array gain and spatial multiplexing offered by Massive MIMO. Since its inception, the coherent interference caused by pilot contamination has been believed to create a finite capacity limit, as the number of antennas goes to infinity. In this paper, we prove that this is incorrect and an artifact from using simplistic channel models and suboptimal precoding/combining schemes. We show that with multicell MMSE precoding/combining and a tiny amount of spatial channel correlation or large-scale fading variations over the array, the capacity increases without bound as the number of antennas increases, even under pilot contamination. More precisely, the result holds when the channel covariance matrices of the contaminating users are asymptotically linearly independent, which is generally the case. If also the diagonals of the covariance matrices are linearly independent, it is sufficient to know these diagonals (and not the full covariance matrices) to achieve an unlimited asymptotic capacity.

  • 60.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Hoydis, Jakob
    Nokia Bell Labs, France.
    Sanguinetti, Luca
    University of Pisa, Italy / CentraleSupelec, France.
    Massive MIMO Networks: spectral, energy, and hardware efficiency2018Book (Refereed)
    Abstract [en]

    Massive multiple-input multiple-output (Massive MIMO) is the latest technology that will improve the speed and throughput of wireless communication systems for years to come. Whilst there may be some debate over the origins of the term Massive MIMO and what it precisely means, this monograph describes in detail how the research conducted in the past decades lead to a scalable multiantenna technology that offers great throughput and energy efficiency under practical conditions. Written for students, practicing engineers and researchers who want to learn the conceptual and analytical foundations of Massive MIMO, in terms of spectral, energy, and/or hardware efficiency, as well as channel estimation and practical considerations, it provides a clear and tutorial like exposition of all the major topics. It also connects the dots of the research literature covering numerous topics not easily found therein. Massive MIMO Networks is the first monograph on the subject to cover the spatial chan el correlation and consider rigorous signal processing design essential for the complete understanding by its target audience.

  • 61.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. Nokia Bell Labs, France.
    Hoydis, Jakob
    Nokia Bell Labs, Nozay, France.
    Sanguinetti, Luca
    Univ Pisa, Italy; Univ Paris Saclay, France.
    Pilot Contamination is Not a Fundamental Asymptotic Limitation in Massive MIMO2017In: 2017 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    Massive MIMO (multiple-input multiple-output) provides great improvements in spectral efficiency over legacy cellular networks, by coherent combining of the signals over a large antenna array and by spatial multiplexing of many users. Since its inception, the coherent interference caused by pilot contamination has been believed to be an impairment that does not vanish, even with an unlimited number of antennas. In this work, we show that this belief is incorrect and an artifact from using simplistic channel models and suboptimal signal processing schemes. We focus on the uplink and prove that with multicell MMSE combining, the spectral efficiency grows without bound as the number of antennas increases, even under pilot contamination, under a condition of linear independence between the channel covariance matrices. This condition is generally satisfied, except in special cases that are hardly found in practice.

  • 62.
    Björnson, Emil
    et al.
    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.
    How Energy-Efficient Can a Wireless Communication System Become?2018In: 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, IEEE , 2018, p. 1252-1256Conference paper (Refereed)
    Abstract [en]

    The data traffic in wireless networks is steadily growing. The long-term trend follows Coopers law, where the traffic is doubled every Two-and-a-half year, and it will likely continue for decades to come. The data transmission is tightly connected with the energy consumption in the power amplifiers, transceiver hardware, and baseband processing. The relation is captured by the energy efficiency metric, measured in bit/Joule, which describes how much energy is consumed per correctly received information hit. While the data rate is fundamentally limited by the channel capacity, there is currently no clear understanding of how energy-efficient a communication system can become. Current research papers typically present values on the order of 10Mbit/Joule, while previous network generations seem to operate at energy efficiencies on the order of 10 kbit/Joule. Is this roughly as energy-efficient future systems (5G and beyond) can become, or are we still far from the physical limits? These questions are answered in this paper. We analyze a different cases representing potential future deployment and hardware characteristics.

  • 63.
    Björnson, Emil
    et al.
    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.
    Three Practical Aspects of Massive MIMO: Intermittent User Activity, Pilot Synchronism, and Asymmetric Deployment2015In: 2015 IEEE Globecom Workshops (GC Wkshps), Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1-6Conference paper (Refereed)
    Abstract [en]

    This paper considers three aspects of Massive MIMO (multiple- input multiple-output) communication networks that have received little attention in previous works, but are important to understand when designing and implementing this promising wireless technology. First, we analyze how bursty data traffic behaviors affect the system. Using a probabilistic model for intermittent user activity, we show that the spectral efficiency (SE) scales gracefully with reduced user activity. Then, we make an analytic comparison between synchronous and asynchronous pilot signaling, and prove that the choice between these has no impact on the SE. Finally, we provide an analytical and numerical study of the SE achieved with random network deployment.

  • 64.
    Björnson, Emil
    et al.
    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.
    Debbah, Merouane
    CentraleSupelec, France; Huawei, France.
    Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?2016In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 15, no 2, p. 1293-1308Article in journal (Refereed)
    Abstract [en]

    Massive MIMO is a promising technique for increasing the spectral efficiency (SE) of cellular networks, by deploying antenna arrays with hundreds or thousands of active elements at the base stations and performing coherent transceiver processing. A common rule-of-thumb is that these systems should have an order of magnitude more antennas M than scheduled users K because the users channels are likely to be near-orthogonal when M/K > 10. However, it has not been proved that this rule-of-thumb actually maximizes the SE. In this paper, we analyze how the optimal number of scheduled users K-star depends on M and other system parameters. To this end, new SE expressions are derived to enable efficient system-level analysis with power control, arbitrary pilot reuse, and random user locations. The value of K-star in the large-M regime is derived in closed form, while simulations are used to show what happens at finite M, in different interference scenarios, with different pilot reuse factors, and for different processing schemes. Up to half the coherence block should be dedicated to pilots and the optimal M/K is less than 10 in many cases of practical relevance. Interestingly, K-star depends strongly on the processing scheme and hence it is unfair to compare different schemes using the same K.

  • 65.
    Björnson, Emil
    et al.
    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.
    Debbah, Merouane
    CentraleSupelec, France.
    Optimizing Multi-Cell Massive MIMO for Spectral Efficiency: How Many Users Should Be Scheduled?2014In: 2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014, Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 612-616Conference paper (Refereed)
    Abstract [en]

    Massive MIMO is a promising technique to increase the spectral efficiency of cellular networks, by deploying antenna arrays with hundreds or thousands of active elements at the base stations and performing coherent beamforming. A common rule-of-thumb is that these systems should have an order of magnitude more antennas, N, than scheduled users, K, because the users' channels are then likely to be quasi-orthogonal. However, it has not been proved that this rule-of-thumb actually maximizes the spectral efficiency. In this paper, we analyze how the optimal number of scheduled users, K*, depends on N and other system parameters. The value of K* in the large-N regime is derived in closed form, while simulations are used to show what happens at finite N, in different interference scenarios, and for different beamforming.

  • 66.
    Björnson, Emil
    et al.
    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.
    Marzetta, Thomas L.
    Nokia, France.
    Massive MIMO: Ten Myths and One Critical Question2016In: IEEE Communications Magazine, ISSN 0163-6804, E-ISSN 1558-1896, Vol. 54, no 2, p. 114-123Article in journal (Refereed)
    Abstract [en]

    Wireless communications is one of the most successful technologies in modern years, given that an exponential growth rate in wireless traffic has been sustained for over a century (known as Coopers law). This trend will certainly continue, driven by new innovative applications; for example, augmented reality and the Internet of Things. Massive MIMO has been identified as a key technology to handle orders of magnitude more data traffic. Despite the attention it is receiving from the communication community, we have personally witnessed that Massive MIMO is subject to several widespread misunderstandings, as epitomized by following (fictional) abstract: "The Massive MIMO technology uses a nearly infinite number of high-quality antennas at the base stations. By having at least an order of magnitude more antennas than active terminals, one can exploit asymptotic behaviors that some special kinds of wireless channels have. This technology looks great at first sight, but unfortunately the signal processing complexity is off the charts and the antenna arrays would be so huge that it can only be implemented in millimeter-wave bands." These statements are, in fact, completely false. In this overview article, we identify 10 myths and explain why they are not true. We also ask a question that is critical for the practical adoption of the technology and which will require intense future research activities to answer properly. We provide references to key technical papers that support our claims, while a further list of related overview and technical papers can be found at the Massive MIMO Info Point: http://massivemimo.eu

  • 67.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Matthaiou, Michail
    Chalmers, Sweden; Queens University of Belfast, North Ireland.
    Pitarokoilis, Antonios
    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.
    Distributed Massive MIMO in Cellular Networks: Impact of Imperfect Hardware and Number of Oscillators2015In: 23rd European Signal Processing Conference, EUSIPCO 2015, Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 2436-2440Conference paper (Refereed)
    Abstract [en]

    Distributed massive multiple-input multiple-output (MIMO) combines the array gain of coherent MIMO processing with the proximity gains of distributed antenna setups. In this paper, we analyze how transceiver hardware impairments affect the downlink with maximum ratio transmission. We derive closed-form spectral efficiencies expressions and study their asymptotic behavior as the number of the antennas increases. We prove a scaling law on the hardware quality, which reveals that massive MIMO is resilient to additive distortions, while multiplicative phase noise is a limiting factor. It is also better to have separate oscillators at each antenna than one per BS

  • 68.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    University of Pisa, Italy; University of Paris Saclay, France.
    Debbah, Merouane
    University of Paris Saclay, France; Huawei Technology, France.
    Massive MIMO with Imperfect Channel Covariance Information2016In: 2016 50TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, IEEE COMPUTER SOC , 2016, p. 974-978Conference paper (Refereed)
    Abstract [en]

    This work investigates the impact of imperfect statistical information in the uplink of massive MIMO systems. In particular, we first show why covariance information is needed and then propose two schemes for covariance matrix estimation. A lower bound on the spectral efficiency (SE) of any combining scheme is derived, under imperfect covariance knowledge, and a closed-form expression is computed for maximum-ratio combining. We show that having covariance information is not critical, but that it is relatively easy to acquire it and to achieve SE close to the ideal case of having perfect statistical information.

  • 69.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    Univ Pisa, Italy.
    Hoydis, Jakob
    Nokia Bell Labs, France.
    Can Hardware Distortion Correlation be Neglected When Analyzing Uplink SE in Massive MIMO?2018In: 2018 IEEE 19TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2018, p. 221-225Conference paper (Refereed)
    Abstract [en]

    This paper analyzes how the distortion created by hardware impairments in a multiple-antenna base station affects the uplink spectral efficiency (SE), with focus on Massive MIMO. The distortion is correlated across the antennas, but has been often approximated as uncorrelated to facilitate (tractable) SE analysis. To determine when this approximation is accurate, basic properties of the distortion correlation are first uncovered. Then, we focus on third-order non-linearities and prove analytically and numerically that the correlation can be neglected in the SE analysis when there are many users. In i.i.d. Rayleigh fading with equal signal-to-noise ratios, this occurs when having five users.

  • 70.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    Univ Pisa, Italy.
    Hoydis, Jakob
    Paris Saclay, France.
    Hardware Distortion Correlation Has Negligible Impact on UL Massive MIMO Spectral Efficiency2019In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 67, no 2, p. 1085-1098Article in journal (Refereed)
    Abstract [en]

    This paper analyzes how the distortion created by hardware impairments in a multiple-antenna base station affects the uplink spectral efficiency (SE), with a focus on massive multiple input multiple output (MIMO). This distortion is correlated across the antennas but has been often approximated as uncorrelated to facilitate (tractable) SE analysis. To determine when this approximation is accurate, basic properties of distortion correlation are first uncovered. Then, we separately analyze the distortion correlation caused by third-order non-linearities and by quantization. Finally, we study the SE numerically and show that the distortion correlation can be safely neglected in massive MIMO when there are sufficiently many users. Under independent identically distributed Rayleigh fading and equal signal-to-noise ratios (SNRs), this occurs for more than five transmitting users. Other channel models and SNR variations have only minor impact on the accuracy. We also demonstrate the importance of taking the distortion characteristics into account in the receive combining.

  • 71.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. KTH Royal Institute Technology, Sweden; Supelec, France.
    Sanguinetti, Luca
    University of Pisa, Italy; CentraleSupelec, France.
    Hoydis, Jakob
    Bell Labs, Germany.
    Debbah, Merouane
    CentraleSupelec, France.
    Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer?2015In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 14, no 6, p. 3059-3075Article in journal (Refereed)
    Abstract [en]

    Assume that a multi-user multiple-input multiple-output (MIMO) system is designed from scratch to uniformly cover a given area with maximal energy efficiency (EE). What are the optimal number of antennas, active users, and transmit power? The aim of this paper is to answer this fundamental question. We consider jointly the uplink and downlink with different processing schemes at the base station and propose a new realistic power consumption model that reveals how the above parameters affect the EE. Closed-form expressions for the EE-optimal value of each parameter, when the other two are fixed, are provided for zero-forcing (ZF) processing in single-cell scenarios. These expressions prove how the parameters interact. For example, in sharp contrast to common belief, the transmit power is found to increase (not to decrease) with the number of antennas. This implies that energy-efficient systems can operate in high signal-to-noise ratio regimes in which interference-suppressing signal processing is mandatory. Numerical and analytical results show that the maximal EE is achieved by a massive MIMO setup wherein hundreds of antennas are deployed to serve a relatively large number of users using ZF processing. The numerical results show the same behavior under imperfect channel state information and in symmetric multi-cell scenarios.

  • 72.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    University of Pisa, Italy; University of Paris Saclay, France.
    Kountouris, Marios
    Huawei Technology Co Ltd, France.
    Deploying Dense Networks for Maximal Energy Efficiency: Small Cells Meet Massive MIMO2016In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 34, no 4, p. 832-847Article in journal (Refereed)
    Abstract [en]

    What would a cellular network designed for maximal energy efficiency look like? To answer this fundamental question, tools from stochastic geometry are used in this paper to model future cellular networks and obtain a new lower bound on the average uplink spectral efficiency. This enables us to formulate a tractable uplink energy efficiency (EE) maximization problem and solve it analytically with respect to the density of base stations (BSs), the transmit power levels, the number of BS antennas and users per cell, and the pilot reuse factor. The closed-form expressions obtained from this general EE maximization framework provide valuable insights on the interplay between the optimization variables, hardware characteristics, and propagation environment. Small cells are proved to give high EE, but the EE improvement saturates quickly with the BS density. Interestingly, the maximal EE is achieved by also equipping the BSs with multiple antennas and operate in a "massive MIMO" fashion, where the array gain from coherent detection mitigates interference and the multiplexing of many users reduces the energy cost per user.

  • 73.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    University of Pisa, Italy; CentraleSupelec, France.
    Kountouris, Marios
    CentraleSupelec, France.
    Designing Wireless Broadband Access for Energy Efficiency: Are Small Cells the Only Answer?2015In: 2015 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION WORKSHOP, Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 136-141Conference paper (Refereed)
  • 74.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    University of Pisa, Italy; Central Supelec, France.
    Kountouris, Marios
    Huawei Technology Co Ltd, Peoples R China.
    Energy-Efficient Future Wireless Networks: A Marriage between Massive MIMO and Small Cells2015In: 2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE , 2015, p. 211-215Conference paper (Refereed)
    Abstract [en]

    How would a cellular network designed for high energy efficiency look like? To answer this fundamental question, we model cellular networks using stochastic geometry and optimize the energy efficiency with respect to the density of base stations, the number of antennas and users per cell, the transmit power levels, and the pilot reuse. The highest efficiency is neither achieved by a pure small-cell approach, nor by a pure massive MIMO solution. Interestingly, it is the combination of these approaches that provides the highest energy efficiency; small cells contributes by reducing the propagation losses while massive MIMO enables multiplexing of users with controlled interference.

  • 75.
    Björnson, Emil
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Van der Perre, Liesbet
    Katholieke Univ Leuven, Belgium; Lund Univ, Sweden.
    Buzzi, Stefano
    Univ Cassino and Lazio Merid, Italy; CNIT, Italy.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Massive MIMO in Sub-6 GHz and mmWave: Physical, Practical, and Use-Case Differences2019In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 26, no 2, p. 100-108Article in journal (Refereed)
    Abstract [en]

    The use of base stations (BSs) and access points (APs) with a large number of antennas, called Massive MIMO (multiple-input multiple-output), is a key technology for increasing the capacity of 5G networks and beyond. While originally conceived for conventional sub-6 GHz frequencies, Massive MIMO (mMIMO) is also ideal for frequency bands in the range 30-300 GHz, known as millimeter wave (mmWave). Despite conceptual similarities, the way in which mMIMO can be exploited in these bands is radically different, due to their specific propagation behaviors and hardware characteristics. This article reviews these differences and their implications, while dispelling common misunderstandings. Building on this foundation, we suggest appropriate signal processing schemes and use cases to efficiently exploit mMIMO in both frequency bands.

  • 76.
    Blad, Anton
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Axell, Erik
    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 OFDM Signals in the Presence of CFO: New Algorithms and Empirical Evaluation Using USRP2012In: Proceedings of the 13th IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), IEEE , 2012, p. 159-163Conference paper (Refereed)
    Abstract [en]

    In this work, we consider spectrum sensing of OFDM signals. We deal withthe inevitable problem of a carrier frequency offset, and propose modificationsto some state-of-the-art detectors to cope with that. Moreover, the (modified)detectors are implemented using GNU radio and USRP, and evaluated over aphysical radio channel. Measurements show that all of the evaluated detectorsperform quite well, and the preferred choice of detector depends on thedetection requirements and the radio environment.

  • 77.
    Boyvalenkov, P.
    et al.
    Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Sofia, Bulgaria; Faculty of Engineering, South-Western University, Blagoevgrad, Bulgaria.
    Danev, Danyo
    Linköping University, Department of Electrical Engineering, Communication Systems.
    Stoyanova, M.
    Faculty of Mathematics and Informatics, Sofia University, Sofia, Bulgaria.
    Refinements of Levenshtein Bounds in q-ary Hamming Spaces2018In: Problems of Information Transmission, ISSN 0032-9460, E-ISSN 1608-3253, Vol. 54, no 4, p. 329-342Article in journal (Refereed)
    Abstract [en]

    We develop refinements of the Levenshtein bound in q-ary Hamming spaces by taking into account the discrete nature of the distances versus the continuous behavior of certain parameters used by Levenshtein. We investigate the first relevant cases and present new bounds. In particular, we derive generalizations and q-ary analogs of the MacEliece bound. Furthermore, we provide evidence that our approach is as good as the complete linear programming and discuss how faster are our calculations. Finally, we present a table with parameters of codes which, if exist, would attain our bounds.

  • 78.
    Carlsson, Robin
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Investigation and Implementation of Coexistence Tool for Antennas2014Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    With the increase of the number of radios and antennas on today’s systems, the risk of co-site interference is very high. Intermodulation product and antenna coupling are two common sources of interference. The thesis investigates some features of a radio system, like antenna types, receiver parameters, intermodulation products and isolation, and suggests how this knowledge can be used to minimize the risk of co-site interference. The goal is to maximize the isolation between the antennas, by good frequency planning, the use of filters and taking great care in antenna placement. A first version of an analysis software was developed where transmitters and receivers can be paired and evaluated. An intermodulation product calculator was also implemented, to easily find which products are an issue and where they originate. The goal of the software is to be simple to use and easy to adapt to different setups and situations. It should also be easy to upgrade with new features.

  • 79.
    Chaitanya, Tumula
    et al.
    McGill University, Canada .
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Adaptive power allocation for HARQ with Chase combining in correlated Rayleigh fading channels2014In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 3, no 2, p. 169-172Article in journal (Refereed)
    Abstract [en]

    We consider the problem of minimizing the packet drop probability (PDP) under an average transmit power constraint for Chase combining (CC)-based hybrid-automatic repeat request (HARQ) schemes in correlated Rayleigh fading channels. We propose a method to find a solution to the non-convex optimization problem using an exact expression of the outage probability. However, the complexity of this method is high. Therefore, we propose an alternative approach in which we use an asymptotically equivalent expression for the outage probability and reformulate it as a geometric programming problem (GPP), which can be efficiently solved using convex optimization algorithms.

  • 80.
    Chandhar, Prabhu
    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.
    Massive MIMO as Enabler for Communications with Drone Swarms2016In: 2016 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS), IEEE , 2016, p. 347-354Conference paper (Refereed)
    Abstract [en]

    Massive multiple-input multiple-output (MIMO) is an emerging technology for mobile communications, where a large number of antennas are employed at the base station to simultaneously serve multiple single-antenna terminals with very high capacity. In this paper, we study the potentials and challenges of utilizing massive MIMO for unmanned aerial vehicles (UAVs) communication. We consider a scenario where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Speci[1]cally, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight (LoS) conditions. We also study the type of antenna polarization that should be used in order to maintain a reliable communication link between the GS and the UAVs. The results obtained using a realistic geometric model show that massive MIMO is a potential enabler for high-capacity UAV network

  • 81.
    Chandhar, Prabhu
    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.
    Massive MIMO for Communications With Drone Swarms2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 3, p. 1604-1629Article in journal (Refereed)
    Abstract [en]

    We illustrate the potential of Massive MIMO for communication with unmanned aerial vehicles (UAVs). We consider a scenario, where multiple single-antenna UAVs simultaneously communicate with a ground station (GS) equipped with a large number of antennas. Specifically, we discuss the achievable uplink (UAV to GS) capacity performance in the case of line-of-sight conditions. We develop a realistic geometric model, which incorporates an arbitrary orientation, of the GS and UAV antenna elements to characterize the polarization mismatch loss, which occurs due to the movement and orientation of the UAVs. A closed-form expression for a lower bound on the ergodic rate for a maximum-ratio combining receiver with estimated channel state information is derived. The optimal antenna spacing that maximizes the ergodic rate achieved by an UAV is also determined for uniform linear and rectangular arrays. It is shown that when the UAVs are spherically uniformly distributed around the GS, the ergodic rate per UAV is maximized for an antenna spacing equal to an integer multiple of one-half wavelength.

  • 82.
    Chandhar, Prabhu
    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.
    On Ergodic Rates and Optimal Array Geometry in Line-of-Sight Massive MIMO2016Conference paper (Refereed)
    Abstract [en]

    We investigate the achievable ergodic rate of Massive multi-input-multi-output (MIMO) system in environments with high mobility and line-of-sight (LoS). A 3-dimensional geometric model with uniform rectangular array at the basestation (BS) is used for the investigation. We derive a closed formexpression for a lower bound on the uplink ergodic rate takinginto account imperfections of the channel state information,number of BS antennas, antenna spacing, and spatial distributionof user terminals. The results show that, in LoS Massive MIMO, when the terminals are spherically uniformly distributed around the BS, the ergodic rate is maximized for antenna spacing equal to integer multiples of one-half wavelength.

  • 83.
    Chandhar, Prabhu
    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.
    On the Outage Capacity in Massive MIMO with Line-of-Sight2017In: 2017 IEEE 18TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    We analyze the outage capacity performance of the Massive MIMO uplink in a random line-of-sight (LoS) scenario. Considering a maximum-ratio combining receiver and assuming perfect channel state information at the base station (BS), we derive closed-form expressions for a lower bound on the outage capacity. It is shown that the outage capacity of Massive MIMO in the random LoS scenario logarithmically increases with the number of BS antennas due to the fact that the fluctuations in the total interference power become negligible (i.e., an interference hardening effect).

  • 84.
    Chandhar, Prabhu
    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.
    On the Zero-Forcing Receiver Performance for Massive MIMO Drone Communications2018In: 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 930-934Conference paper (Refereed)
    Abstract [en]

    We study the uplink ergodic rate performance of the zero-forcing (ZF) receiver in a Massive multiple-input and multiple-output (MIMO) enabled drone communication system. Considering a 3D geometric model for line-of-sight (LoS) propagation, approximate but accurate analyses of lower and upper bounds on the uplink ergodic rate with estimated channel state information (CSI) are provided.

  • 85.
    Chandhar, Prabhu
    et al.
    Chandhar Res Labs, India.
    Larsson, Erik G
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Massive MIMO for Connectivity With Drones: Case Studies and Future Directions2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 94676-94691Article in journal (Refereed)
    Abstract [en]

    Unmanned aerial vehicles (UAVs), also known as drones, are proliferating. Applications, such as surveillance, disaster management, and drone racing, place high requirements on the communication with the drones in terms of throughput, reliability, and latency. The existing wireless technologies, notably Wi-Fi, that are currently used for drone connectivity are limited to short ranges and low-mobility situations. New, scalable technology is needed to meet future demands on long connectivity ranges, support for fast-moving drones, and the possibility to simultaneously communicate with entire swarms of drones. Massive multiple-input and multiple-output (MIMO), the main technology component of emerging 5G standards, has the potential to meet these requirements.

  • 86.
    Chandhar, Prabhu
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sekhar Das, Suvra
    Indian Institute Technology, India.
    Multi-Objective Framework for Dynamic Optimization of OFDMA Cellular Systems2016In: IEEE Access, E-ISSN 2169-3536, Vol. 4, p. 1889-1914Article in journal (Refereed)
    Abstract [en]

    Green cellular networking has become an important research area in recent years due to environmental and economical concerns. Switching OFF underutilized base stations (BSs) during oFF-peak traffic load conditions is a promising approach to reduce energy consumption in cellular networks. In practice, during initial cell planning, the BS locations and radio access network (RAN) parameters (BS transmit power, antenna height, and antenna tilt) are optimized to meet the basic system design requirements, such as coverage, capacity, overlap, quality of service (QoS), and so on. As these metrics are tightly coupled with each other due to co-channel interference, switching OFF certain BSs may affect the system requirements. Therefore, identifying a subset of large number of BSs, which are to be put into the sleep mode, is a challenging dynamic optimization problem. In this paper, we develop a multi-objective framework for dynamic optimization framework for orthogonal frequency division multiple access-based cellular systems. The objective is to identify the appropriate set of active sectors and RAN parameters that maximize coverage and area spectral efficiency, while minimizing overlap and area power consumption without violating the QoS requirements for a given traffic demand density. The objective functions and constraints are obtained using appropriate analytical models, which capture the traffic characteristics, propagation characteristics (path-loss, shadowing, and small-scale fading), as well as load condition in neighboring cells. A low-complexity evolutionary algorithm is used for identifying the global Pareto optimal solutions at a faster convergence rate. The inter-relationships between the system objectives are studied, and the guidelines are provided to find an appropriate network configuration that provides the best achievable tradeoffs. The results show that using the proposed framework, significant amount of energy saving can be achieved and with a low computational complexity while maintaining good tradeoffs among the other objectives.

  • 87.
    Chen, Bolin
    et al.
    Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, UK.
    Chen, Zheng
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Pappas, Nikolaos
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Yuan, Di
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Zhang, Jie
    Department of Electronic and Electrical Engineering, The University of Sheffield, Sheffield, UK.
    Modeling and Analysis of MPTCP Proxy-based LTE-WLAN Path Aggregation2017In: 2017 IEEE Global Communications Conference (GLOBECOM), Proceedings Singapore 4 – 8 December 2017, IEEE Communications Society, 2017, p. 1-7Conference paper (Refereed)
    Abstract [en]

    Long Term Evolution (LTE)-Wireless Local Area Network (WLAN) Path Aggregation (LWPA) based on Multi- path Transmission Control Protocol (MPTCP) has been under standardization procedure as a promising and cost-efficient solution to boost Downlink (DL) data rate and handle the rapidly increasing data traffic. This paper aims at providing tractable analysis for the DL performance evaluation of large-scale LWPA networks with the help of tools from stochastic geometry. We consider a simple yet practical model to determine under which conditions a native WLAN Access Point (AP) will work under LWPA mode to help increasing the received data rate. Using stochastic spatial models for the distribution of WLAN APs and LTE Base Stations (BSs), we analyze the density of active LWPA- mode WiFi APs in the considered network model, which further leads to closed-form expressions on the DL data rate and area spectral efficiency (ASE) improvement. Our numerical results illustrate the impact of different network parameters on the performance of LWPA networks, which can be useful for further performance optimization. 

  • 88.
    Chen, Bolin
    et al.
    Univ Sheffield, England.
    Pappas, Nikolaos
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Chen, Zheng
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Yuan, Di
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Zhang, Jie
    Univ Sheffield, England.
    LTE-WLAN Aggregation with Bursty Data Traffic and Randomized Flow Splitting2019In: ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE , 2019Conference paper (Refereed)
    Abstract [en]

    We investigate the effect of bursty traffic in an LTE and Wi-Fi aggregation (LWA)-enabled network, where part of the LTE traffic is offloaded to Wi-Fi access points (APs) to boost the performance of LTE networks. A Wi-Fi AP maintains two queues containing data intended for the LWA-mode user and the native Wi-Fi user, and it is allowed to serve them simultaneously by using superposition coding (SC). With respect to the existing works on LWA, the novelty of our study consists of a random access protocol allowing the Wi-Fi AP to serve the native Wi-Fi user with probabilities that depend on the queue size of the LWA-mode data. We analyze the throughput of the native Wi-Fi network, accounting for different transmitting probabilities of the queues, the traffic flow splitting between LTE and Wi-Fi, and the operating mode of the LWA user with both LTE and Wi-Fi interfaces. Our results provide fundamental insights in the throughput behavior of such aggregated systems, which are essential for further investigation in larger topologies.

  • 89.
    Chen, Bolin
    et al.
    Univ Sheffield, England.
    Pappas, Nikolaos
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Chen, Zheng
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Yuan, Di
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Zhang, Jie
    Univ Sheffield, England.
    Throughput and Delay Analysis of LWA With Bursty Traffic and Randomized Flow Splitting2019In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 24667-24678Article in journal (Refereed)
    Abstract [en]

    We investigate the effect of bursty traffic in a long term evolution (LTE) and Wi-Fi aggregation (LWA)-enabled network. The LTE base station routes packets of the same IP flow through the LIE and Wi-Fi links independently. We motivate the use of superposition coding at the LWA-mode Wi-Fi access point (AP) so that it can serve LWA users and Wi-Fi users simultaneously. A random access protocol is applied in such system, which allows the native-mode AP to access the channel with probabilities that depend on the queue size of the LWA-mode AP to avoid impeding the performance of the LWA-enabled network. We analyze the throughput of the native Wi-Fi network and the delay experienced by the LWA users, accounting for the native-mode AP access probability, the traffic flow splitting between LTE and Wi-Fi, and the operating mode of the LWA user with both LIE and Wi-Fi interfaces. Our results show some fundamental tradeoffs in the throughput and delay behavior of LWA-enabled networks, which provide meaningful insight into the operation of such aggregated systems.

  • 90.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Can We Rely on Channel Hardening in Cell-Free Massive MIMO?2017In: 2017 IEEE GLOBECOM WORKSHOPS (GC WKSHPS), IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    Channel hardening makes fading multi-antenna channels behave as deterministic when there are many antennas. Massive MIMO systems utilize this phenomenon to deliver high and reliable performance from cellular access points. Recently, an alternative form of Massive MIMO has appeared: Cell-Free (CF) Massive MIMO. It is based on having many access points (APs) distributed over a large geographical area and these jointly serve all the users. Since the AP antennas are distributed, instead of co-located, it is not clear if these systems will inherit the channel hardening. In this paper, we use stochastic geometry to investigate this problem. Our results show that the amount of channel hardening is strongly affected by the number of antennas per AP and the propagation environment. To achieve channel hardening in CF Massive MIMO, it is beneficial to have multiple antennas per AP and a small path-loss exponent.

  • 91.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Channel Hardening and Favorable Propagation in Cell-Free Massive MIMO With Stochastic Geometry2018In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 66, no 11, p. 5205-5219Article in journal (Refereed)
    Abstract [en]

    Cell-free (CF) massive multiple-input multiple-output (MIMO) is an alternative topology for future wireless networks, where a large number of single-antenna access points (APs) are distributed over the coverage area. There are no cells but all users are jointly served by the APs using network MIMO methods. Prior works have claimed that the CF massive MIMO inherits the basic properties of cellular massive MIMO, namely, channel hardening and favorable propagation. In this paper, we evaluate if one can rely on these properties when having a realistic stochastic AP deployment. Our results show that channel hardening only appears in special cases, for example, when the pathloss exponent is small. However, by using 5-10 antennas per AP, instead of one, we can substantially improve the hardening. Only spatially well-separated users will exhibit favorable propagation, but when adding more antennas and/or reducing the pathloss exponent, it becomes more likely for favorable propagation to occur. The conclusion is that we cannot rely on the channel hardening and the favorable propagation when analyzing and designing the CF massive MIMO networks, but we need to use achievable rate expressions and resource allocation schemes that work well also in the absence of these properties. Some options are reviewed in this paper.

  • 92.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    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.
    Dynamic Scheduling and Power Control in Uplink Massive MIMO with Random Data Arrivals2019In: ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE , 2019Conference paper (Refereed)
    Abstract [en]

    In this paper, we study the joint power control and scheduling in uplink massive multiple-input multiple-output (MIMO) systems with random data arrivals. The data is generated at each user according to an individual stochastic process. Using Lyapunov optimization techniques, we develop a dynamic scheduling algorithm (DSA), which decides at each time slot the amount of data to admit to the transmission queues and the transmission rates over the wireless channel. The proposed algorithm achieves nearly optimal performance on the long-term user throughput under various fairness policies. Simulation results show that the DSA can improve the time-average delay performance compared to the state-of-the-art power control schemes developed for Massive MIMO with infinite backlogs.

  • 93.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    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.
    When Is the Achievable Rate Region Convex in Two-User Massive MIMO Systems?2018In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 7, no 5, p. 796-799Article in journal (Refereed)
    Abstract [en]

    This letter investigates the achievable rate region in massive multiple-input-multiple-output systems with two users, with a focus on the i.i.d. Rayleigh fading and line-of-sight (LoS) scenarios. If the rate region is convex, spatial multiplexing is preferable to orthogonal scheduling, while the opposite is true for non-convex regions. We prove that the uplink and downlink rate regions with i.i.d. Rayleigh fading are convex, while the convexity in LoS depends on parameters such as angular user separation, number of antennas, and signal-to-noise ratio (SNR).

  • 94.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Kountouris, Marios
    Huawei Technol Co Ltd, France.
    Decentralized Opportunistic Access for D2D Underlaid Cellular Networks2018In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 66, no 10, p. 4842-4853Article in journal (Refereed)
    Abstract [en]

    In this paper, we propose a decentralized access control scheme for interference management in device-to-device (D2D) underlaid cellular networks. Our method combines signal-to-interference ratio (SIR)-aware link activation with cellular guard zones in a system, where D2D links opportunistically access the licensed cellular spectrum when the activation conditions are satisfied. Analytical expressions for the success/coverage probability of both cellular and D2D links are derived. We characterize the impact of the guard zone radius and the SIR threshold on the D2D potential throughput and cellular coverage. A tractable approach is proposed to find the SIR threshold and guard zone radius that maximize the potential throughput of the D2D communication while ensuring sufficient coverage probability for the cellular uplink users. Simulations validate the accuracy of our analytical results and show the performance gain of the proposed scheme compared to prior state-of-the-art solutions.

  • 95.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering. University of Paris Sud, France.
    Lee, Jemin
    Daegu Gyeongbuk Institute Science and Technology, South Korea.
    Quek, Tony Q. S.
    Singapore University of Technology and Design, Singapore.
    Kountouris, Marios
    Huawei Technology France SASU, France.
    Cooperative Caching and Transmission Design in Cluster-Centric Small Cell Networks2017In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 16, no 5, p. 3401-3415Article in journal (Refereed)
    Abstract [en]

    Wireless content caching in small cell networks (SCNs) has recently been considered as an efficient way to reduce the data traffic and the energy consumption of the backhaul in emerging heterogeneous cellular networks. In this paper, we consider a cluster-centric SCN with combined design of cooperative caching and transmission policy. Small base stations (SBSs) are grouped into disjoint clusters, in which in-cluster cache space is utilized as an entity. We propose a combined caching scheme, where part of the cache space in each cluster is reserved for caching the most popular content in every SBS, while the remaining is used for cooperatively caching different partitions of the less popular content in different SBSs, as a means to increase local content diversity. Depending on the availability and placement of the requested content, coordinated multi-point technique with either joint transmission or parallel transmission is used to deliver content to the served user. Using Poisson point process for the SBS location distribution and a hexagonal grid model for the clusters, we provide analytical results on the successful content delivery probability of both transmission schemes for a user located at the cluster center. Our analysis shows an inherent tradeoff between transmission diversity and content diversity in our cooperation design. We also study the optimal cache space assignment for two objective functions: maximization of the cache service performance and the energy efficiency. Simulation results show that the proposed scheme achieves performance gain by leveraging cache-level and signal-level cooperation and adapting to the network environment and user quality-of-service requirements.

  • 96.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Pappas, Nikolaos
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Kountouris, Marios
    Mathematical and Algorithmic Sciences Lab, France Research Center, Huawei Technologies France SASU, Boulogne-Billancourt, France.
    Energy Harvesting in Delay-Aware Cognitive Shared Access Networks2017In: IEEE Workshop on Emerging Energy Harvesting Solutions for 5G Networks (5G-NRG): May 2017, Paris, France., IEEE Press, 2017, p. 168-173Conference paper (Refereed)
    Abstract [en]

    In this work, we study the effect of energy harvesting in a cognitive shared access network with delay constraints on the primary user. We model the distribution of secondary nodes by a homogeneous Poisson point process (PPP), while the primary user is located at fixed location. The secondary users are assumed to have always packets to transmit whilst the primary transmitter has bursty traffic. We assume an energy harvesting zone around the primary transmitter and a guard zone around the primary receiver. The secondary users are transmitting in a random access manner, however, transmissions of secondary nodes are restricted by their battery status and location. Targeting at achieving the maximum secondary throughput under primary delay constraints, we analyze the impact of various parameters on the performance of the considered network. Our results provide insights into the optimization of access protocol parameters for the energy harvesting-based cognitive shared access network with delay constraints.

  • 97.
    Chen, Zheng
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Pappas, Nikolaos
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Kountouris, Marios
    Huawei Technol Co Ltd, France.
    Angelakis, Vangelis
    Linköping University, Department of Science and Technology, Communications and Transport Systems. Linköping University, Faculty of Science & Engineering.
    Throughput With Delay Constraints in a Shared Access Network With Priorities2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 9, p. 5885-5899Article in journal (Refereed)
    Abstract [en]

    In this paper, we analyze a shared access network with a fixed primary node and randomly distributed secondary nodes whose spatial distribution follows a poisson point process. The secondary nodes use a random access protocol allowing them to access the channel with probabilities that depend on the queue size of the primary node. Assuming a system with multipacket reception receivers, having bursty packet arrivals at the primary and saturated traffic at the secondary nodes, our protocol can be tuned to alleviate congestion at the primary. We analyze the throughput of the secondary network and the primary average delay, as well as the impact of the secondary node access probability and transmit power. We formulate an optimization problem to maximize the throughput of the secondary network under delay constraints for the primary node; in the case of no congestion control, the optimal access probability can be provided in closed form. Our numerical results illustrate the effect of network operating parameters on the performance of the proposed priority-based shared access protocol.

  • 98.
    Cheng, Hei Victor
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Aspects of Power Allocation in Massive MIMO2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The past decades have seen a rapid growth of mobile data trac, both in terms of connected devices and data rate. To satisfy the ever growing data trac demand in wireless communication systems, the current cellular systems have to be redesigned to increase both spectral eciency and energy eciency. Massive MIMO (Multiple-Input-Multiple-Output) is one solution that satisfy both requirements. In massive MIMO systems, hundreds of antennas are employed at the base station to provide service to many users at the same time and frequency. This enables the system to serve the users with uniformly good quality of service simultaneously, with low-cost hardware and without using extra bandwidth and energy. To achieve this, proper resource allocation is needed. Among the available resources, transmit power is one of the most important degree of freedom to control the spectral eciency and energy eciency. Due to the use of excessive number of antennas and low-end hardware at the base station, new aspects of power allocation compared to current systems arises. In the rst part of the thesis, a new uplink power allocation schemes that based on long term channel statistics is proposed. Since quality of the channel estimates is crucial in massive MIMO, in addition to data power allocation, joint power allocation that includes the pilot power as additional variable should be considered. Therefore a new framework for power allocation that matches practical systems is developed, as the methods developed in the literature cannot be applied directly to massive MIMO systems. Simulation results conrm the advantages brought by the the proposed new framework. In the second part of the thesis, we investigate the eects of using low-end ampliers at the base stations. The non-linear behavior of power consumption in these ampliers changes the power consumption model at the base station, thereby changes the power allocation. Two dierent scenarios are investigated and both results show that a certain number of antennas can be turned o in low load scenarios.

    List of papers
    1. MIMO Capacity under Power Amplifiers Consumed Power and Per-Antenna Radiated Power Constraints
    Open this publication in new window or tab >>MIMO Capacity under Power Amplifiers Consumed Power and Per-Antenna Radiated Power Constraints
    2014 (English)In: 2014 IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 179-183Conference paper, Published paper (Refereed)
    Abstract [en]

    We investigate the capacity of the multiple-input-multiple-output channel taking into account the consumed power in the power amplifiers. The mutual information is optimized with a limitation of total consumed power and per-antenna radiated power for a fixed channel with full channel state information at both the transmitter and receiver. The capacity is thus obtained by optimizing the input distribution to maximize the mutual information. Since the optimization problem is non-convex, direct computation of the capacity suffers from high computational complexity. Hence upper and lower bounds on the capacity are given as benchmarks for different ad-hoc schemes. An efficient suboptimal algorithm is also presented. Numerical results show that the suboptimal algorithm performs close to the capacity.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2014
    Series
    IEEE International Workshop on Signal Processing Advances in Wireless Communications, ISSN 2325-3789
    Keywords
    MIMO capacity; power amplifier; consumed power constraint; per-antenna power constraint
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-114602 (URN)10.1109/SPAWC.2014.6941397 (DOI)000348859000037 ()9781479949038 (ISBN)9781479939121 (ISBN)9781479949021 (ISBN)
    Conference
    IEEE 15th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC),June 22-25, Toronto, Canada
    Available from: 2015-02-26 Created: 2015-02-26 Last updated: 2016-11-24Bibliographically approved
    2. Massive MIMO at Night: On the Operation of Massive MIMO in Low Traffic Scenarios
    Open this publication in new window or tab >>Massive MIMO at Night: On the Operation of Massive MIMO in Low Traffic Scenarios
    2015 (English)In: 2015 IEEE International Conference on Communications (ICC), IEEE , 2015, p. 1697-1702Conference paper, Published paper (Refereed)
    Abstract [en]

    For both maximum ratio transmission (MRT) and zero forcing (ZF) precoding schemes and given any specific rate requirement the optimal transmit power, number of antennas to be used, number of users to be served and number of pilots spent on channel training are found with the objective to minimize the total consumed power at the base station. The optimization problem is solved by finding closed form expressions of the optimal transmit power and then search over the remaining discrete variables. The analysis consists of two parts, the first part investigates the situation when only power consumed in the RF amplifiers is considered. The second part includes both the power consumed in the RF amplifiers and in other transceiver circuits. In the former case having all antennas active while reducing the transmit power is optimal. Adaptive scheme to switch off some of the antennas at the base stations is found to be optimal in the latter case.

    Place, publisher, year, edition, pages
    IEEE, 2015
    Series
    IEEE International Conference on Communications, ISSN 1550-3607, E-ISSN 1938-1883
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-127290 (URN)10.1109/ICC.2015.7248569 (DOI)000371708101150 ()9781467364324 (ISBN)9781467364317 (ISBN)9781467364300 (ISBN)
    Conference
    IEEE International Conference on Communications (ICC), 8-12 June, London, UK
    Available from: 2016-04-20 Created: 2016-04-19 Last updated: 2019-06-28Bibliographically approved
  • 99.
    Cheng, Hei Victor
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
    Optimizing Massive MIMO: Precoder Design and Power Allocation2018Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The past decades have seen a rapid growth of mobile data traffic,both in terms of connected devices and data rate. To satisfy the evergrowing data traffic demand in wireless communication systems, thecurrent cellular systems have to be redesigned to increase both spectralefficiency and energy efficiency. Massive MIMO(Multiple-Input-Multiple-Output) is one solution that satisfy bothrequirements. In massive MIMO systems, hundreds of antennas areemployed at the base station to provide service to many users at thesame time and frequency. This enables the system to serve the userswith uniformly good quality of service simultaneously, with low-costhardware and without using extra bandwidth and energy. To achievethis, proper resource allocation is needed. Among the availableresources, transmit power beamforming are the most important degrees offreedom to control the spectral efficiency and energy efficiency. Dueto the use of excessive number of antennas and low-end hardware at thebase station, new aspects of power allocation and beamforming compared to currentsystems arises.

    In the first part of the thesis, new uplink power allocation schemes that based on long term channel statistics isproposed. Since quality of the channel estimates is crucial in massive MIMO, in addition to data power allocation, joint power allocationthat includes the pilot power as additional variable should be considered. Therefore a new framework for power allocation thatmatches practical systems is developed, as the methods developed in the literature cannot be applied directly to massive MIMO systems. Simulation results confirm the advantages brought by the the proposed new framework.

    In the second part, we introduces a new approach to solve the joint precoding and power allocation for different objective in downlink scenarios by a combination of random matrix theory and optimization theory. The new approach results in a simplified problem that, though non-convex, obeys a simple separable structure. Simulation results showed that the proposed scheme provides large gains over heuristic solutions when the number of users in the cell is large, which is suitable for applying in massive MIMO systems.

    In the third part we investigate the effects of using low-end amplifiers at the basestations. The non-linear behavior of power consumption in these amplifiers changes the power consumption model at the basestation, thereby changes the power allocation and beamforming design. Different scenarios are investigated and resultsshow that a certain number of antennas can be turned off in some scenarios.

    In the last part we consider the use of non-orthogonal-multiple-access (NOMA) inside massive MIMO systems in practical scenarios where channel state information (CSI) is acquired through pilot signaling. Achievable rate analysis is carried out for different pilot signaling schemes including both uplink and downlink pilots. Numerical results show that when downlink CSI is available at the users, our proposed NOMA scheme outperforms orthogonal schemes. However with more groups of users present in the cell, it is preferable to use multi-user beamforming in stead of NOMA.

    List of papers
    1. Optimal Pilot and Payload Power Control in Single-Cell Massive MIMO Systems
    Open this publication in new window or tab >>Optimal Pilot and Payload Power Control in Single-Cell Massive MIMO Systems
    2017 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 65, no 9, p. 2363-2378Article in journal (Refereed) Published
    Abstract [en]

    This paper considers the jointly optimal pilot and data power allocation in single-cell uplink massive multiple-input-multiple- output systems. Using the spectral efficiency (SE) as performance metric and setting a total energy budget per coherence interval, the power control is formulated as optimization problems for two different objective functions: the weighted minimum SE among the users and the weighted sum SE. A closed form solution for the optimal length of the pilot sequence is derived. The optimal power control policy for the former problem is found by solving a simple equation with a single variable. Utilizing the special structure arising from imperfect channel estimation, a convex reformulation is found to solve the latter problem to global optimality in polynomial time. The gain of the optimal joint power control is theoretically justified, and is proved to be large in the low-SNR regime. Simulation results also show the advantage of optimizing the power control over both pilot and data power, as compared to the cases of using full power and of only optimizing the data powers as done in previous work.

    Place, publisher, year, edition, pages
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2017
    Keywords
    Massive MIMO; power control; power allocation; convex optimization
    National Category
    Control Engineering
    Identifiers
    urn:nbn:se:liu:diva-136034 (URN)10.1109/TSP.2016.2641381 (DOI)000395877600013 ()
    Note

    Funding Agencies|EU [ICT-619086]; ELLIIT; CENIIT

    Available from: 2017-03-27 Created: 2017-03-27 Last updated: 2019-06-28
    2. Massive MIMO at Night: On the Operation of Massive MIMO in Low Traffic Scenarios
    Open this publication in new window or tab >>Massive MIMO at Night: On the Operation of Massive MIMO in Low Traffic Scenarios
    2015 (English)In: 2015 IEEE International Conference on Communications (ICC), IEEE , 2015, p. 1697-1702Conference paper, Published paper (Refereed)
    Abstract [en]

    For both maximum ratio transmission (MRT) and zero forcing (ZF) precoding schemes and given any specific rate requirement the optimal transmit power, number of antennas to be used, number of users to be served and number of pilots spent on channel training are found with the objective to minimize the total consumed power at the base station. The optimization problem is solved by finding closed form expressions of the optimal transmit power and then search over the remaining discrete variables. The analysis consists of two parts, the first part investigates the situation when only power consumed in the RF amplifiers is considered. The second part includes both the power consumed in the RF amplifiers and in other transceiver circuits. In the former case having all antennas active while reducing the transmit power is optimal. Adaptive scheme to switch off some of the antennas at the base stations is found to be optimal in the latter case.

    Place, publisher, year, edition, pages
    IEEE, 2015
    Series
    IEEE International Conference on Communications, ISSN 1550-3607, E-ISSN 1938-1883
    National Category
    Electrical Engineering, Electronic Engineering, Information Engineering
    Identifiers
    urn:nbn:se:liu:diva-127290 (URN)10.1109/ICC.2015.7248569 (DOI)000371708101150 ()9781467364324 (ISBN)9781467364317 (ISBN)9781467364300 (ISBN)
    Conference
    IEEE International Conference on Communications (ICC), 8-12 June, London, UK
    Available from: 2016-04-20 Created: 2016-04-19 Last updated: 2019-06-28Bibliographically approved
    3. Performance Analysis of NOMA in Training-Based Multiuser MIMO Systems
    Open this publication in new window or tab >>Performance Analysis of NOMA in Training-Based Multiuser MIMO Systems
    2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 1, p. 372-385Article in journal (Refereed) Published
    Abstract [en]

    This paper considers the use of non-orthogonal-multiple-access (NOMA) in multiuser MIMO systems in practical scenarios where channel state information (CSI) is acquired through pilot signaling. A new NOMA scheme that uses shared pilots is proposed. Achievable rate analysis is carried out for different pilot signaling schemes, including both uplink and downlink pilots. The achievable rate performance of the proposed NOMA scheme with shared pilot within each group is compared with the traditional orthogonal access scheme with orthogonal pilots. Our proposed scheme is a generalization of the orthogonal scheme, and can be reduced to the orthogonal scheme when appropriate power allocation parameters are chosen. Numerical results show that when downlink CSI is available at the users, our proposed NOMA scheme outperforms orthogonal schemes. However with more groups of users present in the cell, it is preferable to use multi-user beamforming instead of NOMA.

    Place, publisher, year, edition, pages
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
    Keywords
    Multiuser MIMO; NOMA; channel estimation; training; performance analysis
    National Category
    Telecommunications
    Identifiers
    urn:nbn:se:liu:diva-145161 (URN)10.1109/TWC.2017.2767030 (DOI)000422945400028 ()
    Conference
    18th IEEE International Workshop on Signal Processing Advances for Wireless Communications (SPAWC)
    Note

    Funding Agencies|Swedish Research Council; Linkoping University Center for Industrial Information Technology; ELLIIT

    Available from: 2018-02-13 Created: 2018-02-13 Last updated: 2019-06-28
  • 100.
    Cheng, Hei Victor
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    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.
    SEMI-CLOSED FORM SOLUTION FOR SUM RATE MAXIMIZATION IN DOWNLINK MULTIUSER MIMO VIA LARGE-SYSTEM ANALYSIS2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2018, p. 3699-3703Conference paper (Refereed)
    Abstract [en]

    This work introduces a new approach to solve the joint precoding and power allocation for sum rate maximization problem in the downlink multiuser MIMO by a combination of random matrix theory and optimization theory. The new approach results in a simplified problem that, though non-convex, obeys a simple separable structure. The sum rate maximization problem is decomposed into different single-variable optimization problems that can be solved in parallel. A water-filling-like solution is found, which can be applied under some mild conditions on the SNRs of the users. The proposed scheme provides large gains over heuristic solutions when the number of users in the cell is large, which suggests the applicability in massive MIMO systems.

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