liu.seSearch for publications in DiVA
Change search
Refine search result
1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Rows per page
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sort
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
  • Standard (Relevance)
  • Author A-Ö
  • Author Ö-A
  • Title A-Ö
  • Title Ö-A
  • Publication type A-Ö
  • Publication type Ö-A
  • Issued (Oldest first)
  • Issued (Newest first)
  • Created (Oldest first)
  • Created (Newest first)
  • Last updated (Oldest first)
  • Last updated (Newest first)
  • Disputation date (earliest first)
  • Disputation date (latest first)
Select
The maximal number of hits you can export is 250. When you want to export more records please use the Create feeds function.
  • 1.
    Pizzo, Andrea
    et al.
    University of Pisa, Italy.
    Verenzuela, Daniel
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    University of Pisa, Italy.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Network Deployment for Maximal Energy Efficiency in Uplink with Multislope Path Loss2018In: IEEE Transactions on Green Communications and Networking, E-ISSN 2473-2400, Vol. 2, no 3, p. 735-750Article in journal (Refereed)
    Abstract [en]

    This work aims to design the uplink (UL) of a cellular network for maximal energy efficiency (EE). Each base station (BS) is randomly deployed within a given area and is equipped with M antennas to serve K user equipments (UEs). A multislope (distance-dependent) path loss model is considered and linear processing is used, under the assumption that channel state information is acquired by using pilot sequences (reused across the network). Within this setting, a lower bound on the UL spectral efficiency and a realistic circuit power consumption model are used to evaluate the network EE. Numerical results are first used to compute the optimal BS density and pilot reuse factor for a Massive MIMO network with three different detection schemes, namely, maximum ratio combining, zero-forcing (ZF) and multicell minimum mean-squared error. The numerical analysis shows that the EE is a unimodal function of BS density and achieves its maximum for a relatively small density of BS, irrespective of the employed detection scheme. This is in contrast to the single-slope (distance-independent) path loss model, for which the EE is a monotonic non-decreasing function of BS density. Then, we concentrate on ZF and use stochastic geometry to compute a new lower bound on the spectral efficiency, which is then used to optimize, for a given BS density, the pilot reuse factor, number of BS antennas and UEs. Closed-form expressions are computed from which valuable insights into the interplay between optimization variables, hardware characteristics, and propagation environment are obtained.

  • 2.
    Pizzo, Andrea
    et al.
    Univ Pisa, Italy.
    Verenzuela, Daniel
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Sanguinetti, Luca
    Univ Pisa, Italy; Univ Paris Saclay, France.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Network Deployment for Maximal Energy Efficiency in Uplink with Zero-Forcing2017In: GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE, IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    This work aims to design a cellular network for maximal energy efficiency (EE). In particular, we consider the uplink with multi-antenna base stations and assume that zero-forcing (ZF) combining is used for data detection with imperfect channel state information. Using stochastic geometry and a new lower bound on the average per-user spectral efficiency of the network, we optimize the pilot reuse factor, number of antennas and users per base station. Closed-form expressions are computed from which valuable insights into the interplay between the optimization variables, hardware characteristics, and propagation environment are obtained. Numerical results are used to validate the analysis and make comparisons with a network using maximum ratio (MR) combining. The results show that a Massive MIMO setup arises as the EE-optimal network configuration. In addition, ZF provides higher EE than MR while allowing a smaller pilot reuse factor and a more dense network deployment.

  • 3.
    Verenzuela, Daniel
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Analysis of Alternative Massive MIMO Designs: Superimposed Pilots and Mixed-ADCs2018Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    The development of information and communication technologies (ICT) provides the means for reaching global connectivity that can help humanity progress and prosper. This comes with high demands on data traffic and number of connected devices which are rapidly growing and need to be met by technological development. Massive MIMO, where MIMO stands for multiple-input multiple-output, is envisioned as a fundamental component of next generation wireless communications for its ability to provide high spectral and energy efficiency, SE and EE, respectively. The key feature of this technology is the use of a large number of antennas at the base stations (BS) to spatially multiplex several user equipments (UEs).

    In the development of new technologies like Massive MIMO, many design alternatives need to be evaluated and compared in order to find the best operating point with a preferable tradeoff between high performance and low cost. In this thesis, two alternative designs for signal processing and hardware in Massive MIMO are studied and compared with the baseline operation in terms of SE, EE, and power consumption. The first design is called superimposed pilot (SP) transmission and is based on superimposing pilot and data symbols to remove the overhead from pilot transmission and reduce pilot contamination. The second design is mixed analog-to-digital converters (ADCs) and it aims at balancing high performance and low complexity by allowing different ADC bit resolutions across the BS antennas.

    The results show that the baseline operation of Massive MIMO, properly optimized, is the preferred choice. However, SP and mixed ADCs still have room for improvement and further study is needed to ascertain the full capabilities of these alternative designs.

    List of papers
    1. Joint UL and DL Spectral Efficiency Optimization of Superimposed Pilots in Massive MIMO
    Open this publication in new window or tab >>Joint UL and DL Spectral Efficiency Optimization of Superimposed Pilots in Massive MIMO
    2017 (English)In: Proceedings of 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, 2017, p. 1-7Conference paper, Published paper (Refereed)
    Abstract [en]

    The reuse of pilot sequences in a Massive MIMO system leads to pilot contamination, which reduces the channel estimation quality and adds coherent interference in the data transmission. A standard method to reduce pilot contamination, known as regular pilots (RPs), is to increase the pilot overhead and reuse pilots more sparsely in the network. Another approach, denoted as superimposed pilots (SPs), is to send a superposition of pilot and data symbols which allows the system to reuse pilots far more sparsely. This work performs a comparative analysis of RPs and SPs in Massive MIMO considering the joint spectral efficiency (SE) of the uplink (UL) and downlink (DL) communications. A rigorous DL lower bound on the capacity with SPs is derived and multiobjective optimization theory is used to compare the UL and DL SE between RPs and SPs. Numerical results indicate that RPs and SPs give comparable SE when both methods are optimized.

    Place, publisher, year, edition, pages
    IEEE, 2017
    Series
    IEEE Globecom Workshops
    Keywords
    MIMO communication, channel estimation, data communication, optimisation, DL spectral efficiency optimization, SP, channel estimation quality, data symbols, data transmission, joint spectral efficiency, massive MIMO system, pilot contamination, pilot overhead, pilot sequences, superimposed pilots, Antennas, Contamination, Interference, Optimization, Uplink
    National Category
    Telecommunications
    Identifiers
    urn:nbn:se:liu:diva-145678 (URN)10.1109/GLOCOMW.2017.8269159 (DOI)000426984700128 ()9781538639207 (ISBN)9781538639214 (ISBN)
    Conference
    4-8 Dec 2017 Globecom Workshops (GC Wkshps), Singapore, Singapore
    Note

    Funding agencies: Swedish Foundation for Strategic Research (SSF); ERC Starting MORE [305123]; Swedish Research Council; ELLIIT

    Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2020-01-15Bibliographically approved
    2. Hardware Design and Optimal ADC Resolution for Uplink Massive MIMO Systems
    Open this publication in new window or tab >>Hardware Design and Optimal ADC Resolution for Uplink Massive MIMO Systems
    2016 (English)In: IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Rio de Janeiro, Brazil, July 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1-5Conference paper, Published paper (Refereed)
    Abstract [en]

    This work focuses on the hardware design for the efficient operation of Massive multiple-input multiple-output (MIMO) systems. A closed-form uplink achievable data rate expression is derived considering imperfect channel state information (CSI) and hardware impairments. We formulate an optimization problem to maximize the sum data rate subject to a constraint on the total power consumption. A general power consumption model accounting for the level of hardware impairments is utilized. The optimization variables are the number of base station (BS) antennas and the level of impairments per BS antenna. The resolution of the analog-to-digital converter (ADC) is a primary source of such impairments. The results show the trade-off between the number of BS antennas and the level of hardware impairments, which is important for practical hardware design. Moreover, the maximum power consumption can be tuned to achieve maximum energy efficiency (EE). Numerical results suggest that the optimal level of hardware impairments yields ADCs of 4 to 5 quantization bits.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    Series
    Sensor Array and Multichannel Signal Processing Workshop (SAM), E-ISSN 2151-870X ; 2016
    National Category
    Communication Systems
    Identifiers
    urn:nbn:se:liu:diva-137324 (URN)10.1109/SAM.2016.7569654 (DOI)9781509021031 (ISBN)9781509021048 (ISBN)
    Conference
    IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) 2016, 10-13 July 2016, Rio de Janerio, Brazil
    Available from: 2017-05-12 Created: 2017-05-12 Last updated: 2020-01-15Bibliographically approved
  • 4.
    Verenzuela, Daniel
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Exploring Alternative Massive MIMO Designs: Superimposed Pilots and Mixed-ADCs2020Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The development of information and communication technologies (ICT) provides the means for reaching global connectivity that can help humanity progress and prosper. This comes with high demands on data traffic and number of connected devices which are rapidly growing and need to be met by technological development. Massive MIMO, where MIMO stands for multiple-input multiple-output, is a fundamental component of the 5G wireless communication standard for its ability to provide high spectral and energy efficiency, SE and EE, respectively. The key feature of this technology is the use of a large number of antennas at the base stations (BSs) to spatially multiplex several user equipments (UEs).

    In the development of new technologies like Massive MIMO, many design alternatives need to be evaluated and compared in order to find the best operating point with a preferable tradeoff between low cost and complexity. In this thesis, two alternative designs for signal processing and hardware in Massive MIMO are studied and compared with the baseline operation in terms of SE, EE, and power consumption. The first design is called superimposed pilot (SP) transmission and is based on superimposing pilot and data symbols to eliminate the need to reserve dedicated time-frequency resources for pilots. This allows more data to be transmitted and supports longer pilot sequences that, in turn, reduce pilot contamination. The second design is mixed analog-to-digital converters (ADCs) and it aims at balancing the SE performance and the power consumption cost by allowing different ADC bit resolutions across the BS antennas.

    The results show that the Massive MIMO baseline, when properly optimized, is the preferred choice in standard deployments and propagation conditions. However, the SP alternative design can increase the SE compared to the baseline by using the Massive-MIMO iterative channel estimation and decoding (MICED) algorithm proposed in this dissertation. In particular, the SE gains are found in cases with high mobility, high carrier frequencies, or high number of spatially multiplexed UEs. For the mixed-ADCs alternative design, improvements in the SE and EE compared to the Massive MIMO baseline can be achieved in cases with distributed BS antennas where interference suppression techniques are used.

    List of papers
    1. Spectral and Energy Efficiency of Superimposed Pilots in Uplink Massive MIMO
    Open this publication in new window or tab >>Spectral and Energy Efficiency of Superimposed Pilots in Uplink Massive MIMO
    2018 (English)In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 11, p. 7099-7115Article in journal (Refereed) Published
    Abstract [en]

    Next-generation wireless networks aim at providing substantial improvements in spectral efficiency (SE) and energy efficiency (EE). Massive MIMO has been proved to be a viable technology to achieve these goals by spatially multiplexing several users using many base station (BS) antennas. A potential limitation of massive MIMO in multicell systems is pilot contamination, which arises in the channel estimation process from the interference caused by reusing pilots in neighboring cells. A standard method to reduce pilot contamination, known as regular pilot (RP), is to adjust the length of pilot sequences while transmitting data and pilot symbols disjointly. An alternative method, called superimposed pilot (SP), sends a superposition of pilot and data symbols. This allows use of longer pilots which, in turn, reduces pilot contamination. We consider the uplink of a multicell massive MIMO network, with i.i.d. Rayleigh fading channels, using maximum ratio combining and compare RP and SP in terms of SE and EE. To this end, we derive rigorous closed-form achievable rates with SP under a practical random BS deployment. We prove that the reduction of pilot contamination with SP is outweighed by the additional coherent and non-coherent interference. Numerical results show that when both methods are optimized, RP achieves comparable SE and EE to SP in practical scenarios.

    Place, publisher, year, edition, pages
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
    Keywords
    Massive MIMO; spatial multiplexing; spectral efficiency (SE); energy efficiency (EE); superimposed pilots (SP); channel estimation; pilot contamination; achievable rates; stochastic geometry
    National Category
    Telecommunications
    Identifiers
    urn:nbn:se:liu:diva-153185 (URN)10.1109/TWC.2018.2860939 (DOI)000449978700001 ()
    Conference
    36th IEEE Global Communications Conference (GLOBECOM)
    Note

    Funding Agencies|ELLIIT; Swedish Foundation for Strategic Research (SSF); ERC [MORE 305123]

    Available from: 2018-11-30 Created: 2018-11-30 Last updated: 2020-01-15
    2. Joint UL and DL Spectral Efficiency Optimization of Superimposed Pilots in Massive MIMO
    Open this publication in new window or tab >>Joint UL and DL Spectral Efficiency Optimization of Superimposed Pilots in Massive MIMO
    2017 (English)In: Proceedings of 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, 2017, p. 1-7Conference paper, Published paper (Refereed)
    Abstract [en]

    The reuse of pilot sequences in a Massive MIMO system leads to pilot contamination, which reduces the channel estimation quality and adds coherent interference in the data transmission. A standard method to reduce pilot contamination, known as regular pilots (RPs), is to increase the pilot overhead and reuse pilots more sparsely in the network. Another approach, denoted as superimposed pilots (SPs), is to send a superposition of pilot and data symbols which allows the system to reuse pilots far more sparsely. This work performs a comparative analysis of RPs and SPs in Massive MIMO considering the joint spectral efficiency (SE) of the uplink (UL) and downlink (DL) communications. A rigorous DL lower bound on the capacity with SPs is derived and multiobjective optimization theory is used to compare the UL and DL SE between RPs and SPs. Numerical results indicate that RPs and SPs give comparable SE when both methods are optimized.

    Place, publisher, year, edition, pages
    IEEE, 2017
    Series
    IEEE Globecom Workshops
    Keywords
    MIMO communication, channel estimation, data communication, optimisation, DL spectral efficiency optimization, SP, channel estimation quality, data symbols, data transmission, joint spectral efficiency, massive MIMO system, pilot contamination, pilot overhead, pilot sequences, superimposed pilots, Antennas, Contamination, Interference, Optimization, Uplink
    National Category
    Telecommunications
    Identifiers
    urn:nbn:se:liu:diva-145678 (URN)10.1109/GLOCOMW.2017.8269159 (DOI)000426984700128 ()9781538639207 (ISBN)9781538639214 (ISBN)
    Conference
    4-8 Dec 2017 Globecom Workshops (GC Wkshps), Singapore, Singapore
    Note

    Funding agencies: Swedish Foundation for Strategic Research (SSF); ERC Starting MORE [305123]; Swedish Research Council; ELLIIT

    Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2020-01-15Bibliographically approved
    3. Optimal Power Control for Superimposed Pilots in Uplink Massive MIMO Systems
    Open this publication in new window or tab >>Optimal Power Control for Superimposed Pilots in Uplink Massive MIMO Systems
    2018 (English)In: 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 499-503Conference paper, Published paper (Refereed)
    Abstract [en]

    In Massive MIMO, the pilot contamination effect reduces the spectral efficiency (SE) gains and superimposed pilot (SP) transmission has been proposed to mitigate this effect. SP is based on transmitting pilot and data symbols simultaneously to allow for longer pilots and no pilot overhead. This work studies the optimal power control strategies in the uplink of a Massive MIMO system with SP and detection based on maximum ratio combining The optimization objectives arc maximum product of SINRs and max-min fairness, and these problems are reformulated as geometric programs which allow for efficient implementations. The numerical results indicate that the SE gains from the optimal power control with respect to the heuristic statistical channel inversion power control, are more significant when the interference from pilot symbols is subtracted before data detection.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2018
    Series
    Conference Record of the Asilomar Conference on Signals Systems and Computers, ISSN 1058-6393
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-158405 (URN)10.1109/ACSSC.2018.8645504 (DOI)000467845100087 ()2-s2.0-85062964217 (Scopus ID)978-1-5386-9218-9 (ISBN)
    Conference
    52nd Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA, 28-31 Oct. 2018
    Available from: 2019-06-28 Created: 2019-06-28 Last updated: 2020-01-15Bibliographically approved
    4. Massive-MIMO Iterative Channel Estimation and Decoding (MICED) in the Uplink
    Open this publication in new window or tab >>Massive-MIMO Iterative Channel Estimation and Decoding (MICED) in the Uplink
    Show others...
    2019 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, p. 1-1Article in journal (Refereed) Epub ahead of print
    Abstract [en]

    Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE) through spatial multiplexing of users, which requires accurate channel state information. It is often assumed that regular pilots (RP), where a fraction of the time-frequency resources is reserved for pilots, suffices to provide high SE. However, the SE is limited by the pilot overhead and pilot contamination. An alternative is superimposed pilots (SP) where all resources are used for pilots and data. This removes the pilot overhead and reduces pilot contamination by using longer pilots. However, SP suffers from data interference that reduces the SE gains. This paper proposes the Massive-MIMO Iterative Channel Estimation and Decoding (MICED) algorithm where partially decoded data is used as side-information to improve the channel estimation and increase SE. We show that users with precise data estimates can help users with poor data estimates to decode. Numerical results with QPSK modulation and LDPC codes show that the MICED algorithm increases the SE and reduces the block-error-rate with RP and SP compared to conventional methods. The MICED algorithm with SP delivers the highest SE and it is especially effective in scenarios with short coherence blocks like high mobility or high frequencies.

    Place, publisher, year, edition, pages
    Piscataway, New Jersey, US: IEEE, 2019
    Keywords
    Channel estimation, Interference, Time-frequency analysis, Contamination, Signal processing algorithms, Iterative decoding
    National Category
    Signal Processing
    Identifiers
    urn:nbn:se:liu:diva-163132 (URN)10.1109/TCOMM.2019.2947906 (DOI)
    Available from: 2020-01-15 Created: 2020-01-15 Last updated: 2020-01-20Bibliographically approved
    5. Hardware Design and Optimal ADC Resolution for Uplink Massive MIMO Systems
    Open this publication in new window or tab >>Hardware Design and Optimal ADC Resolution for Uplink Massive MIMO Systems
    2016 (English)In: IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Rio de Janeiro, Brazil, July 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1-5Conference paper, Published paper (Refereed)
    Abstract [en]

    This work focuses on the hardware design for the efficient operation of Massive multiple-input multiple-output (MIMO) systems. A closed-form uplink achievable data rate expression is derived considering imperfect channel state information (CSI) and hardware impairments. We formulate an optimization problem to maximize the sum data rate subject to a constraint on the total power consumption. A general power consumption model accounting for the level of hardware impairments is utilized. The optimization variables are the number of base station (BS) antennas and the level of impairments per BS antenna. The resolution of the analog-to-digital converter (ADC) is a primary source of such impairments. The results show the trade-off between the number of BS antennas and the level of hardware impairments, which is important for practical hardware design. Moreover, the maximum power consumption can be tuned to achieve maximum energy efficiency (EE). Numerical results suggest that the optimal level of hardware impairments yields ADCs of 4 to 5 quantization bits.

    Place, publisher, year, edition, pages
    Institute of Electrical and Electronics Engineers (IEEE), 2016
    Series
    Sensor Array and Multichannel Signal Processing Workshop (SAM), E-ISSN 2151-870X ; 2016
    National Category
    Communication Systems
    Identifiers
    urn:nbn:se:liu:diva-137324 (URN)10.1109/SAM.2016.7569654 (DOI)9781509021031 (ISBN)9781509021048 (ISBN)
    Conference
    IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) 2016, 10-13 July 2016, Rio de Janerio, Brazil
    Available from: 2017-05-12 Created: 2017-05-12 Last updated: 2020-01-15Bibliographically approved
    6. Per-antenna hardware optimization and mixed resolution ADCs in uplink massive MIMO
    Open this publication in new window or tab >>Per-antenna hardware optimization and mixed resolution ADCs in uplink massive MIMO
    2017 (English)In: Conference Record of The Fifty-FirstAsilomar Conference on Signals, Systems & Computers / [ed] Michael B. Matthews, IEEE conference proceedings, 2017, p. 27-31Conference paper, Published paper (Refereed)
    Abstract [en]

    Massive multiple-input multiple-output (MIMO) is a key technology for next generation wireless networks that deploys many antennas at the base stations (BSs). This requires low-complexity hardware at each antenna branch that, in turn, increases distortions. This work studies the selection of per-antenna hardware quality in terms of analog-to-digital converters (ADCs) resolution. A new achievable spectral efficiency (SE) expression is derived and majorization theory is used to analyze the order preserving properties of the SE and the power consumption with respect to the per-antenna ADC resolutions. That is, given a fixed sum of ADC resolutions across the antenna array, is it preferable to use an equal-ADC over a mixed-ADC approach? The results show that having equal-resolution ADCs across the antenna array maximizes the SE and minimizes the power consumption.

    Place, publisher, year, edition, pages
    IEEE conference proceedings, 2017
    Series
    Signals, Systems & Computers, E-ISSN 2576-2303 ; 2017
    Keywords
    Distortion, Hardware, MIMO communication, Power demand, Antenna arrays, Complexity theory
    National Category
    Telecommunications Signal Processing Communication Systems
    Identifiers
    urn:nbn:se:liu:diva-148777 (URN)10.1109/ACSSC.2017.8335129 (DOI)000442659900005 ()9781538618233 (ISBN)9781538606667 (ISBN)9781538618240 (ISBN)
    Conference
    2017 51st Asilomar Conference on Signals, Systems, and Computers. Pacific Grove, CA, USA. 29 Oct.-1 Nov. 2017
    Funder
    ELLIIT - The Linköping‐Lund Initiative on IT and Mobile CommunicationsSwedish Foundation for Strategic Research
    Note

    Funding agencies: EPSRC [EP/P000673/1]

    Available from: 2018-06-19 Created: 2018-06-19 Last updated: 2020-01-15Bibliographically approved
  • 5.
    Verenzuela, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Bergström, Andreas
    Linköping University, Department of Electrical Engineering, Automatic Control. Linköping University, Faculty of Science & Engineering.
    Björnson, Emil
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Optimal Power Control for Superimposed Pilots in Uplink Massive MIMO Systems2018In: 2018 CONFERENCE RECORD OF 52ND ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS, AND COMPUTERS, Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 499-503Conference paper (Refereed)
    Abstract [en]

    In Massive MIMO, the pilot contamination effect reduces the spectral efficiency (SE) gains and superimposed pilot (SP) transmission has been proposed to mitigate this effect. SP is based on transmitting pilot and data symbols simultaneously to allow for longer pilots and no pilot overhead. This work studies the optimal power control strategies in the uplink of a Massive MIMO system with SP and detection based on maximum ratio combining The optimization objectives arc maximum product of SINRs and max-min fairness, and these problems are reformulated as geometric programs which allow for efficient implementations. The numerical results indicate that the SE gains from the optimal power control with respect to the heuristic statistical channel inversion power control, are more significant when the interference from pilot symbols is subtracted before data detection.

  • 6.
    Verenzuela, Daniel
    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.
    Matthaiou, Michail
    Institute of Electronics, Communications and Information Technology (ECIT), Queen’s University Belfast, Northern Ireland .
    Hardware Design and Optimal ADC Resolution for Uplink Massive MIMO Systems2016In: IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Rio de Janeiro, Brazil, July 2016, Institute of Electrical and Electronics Engineers (IEEE), 2016, p. 1-5Conference paper (Refereed)
    Abstract [en]

    This work focuses on the hardware design for the efficient operation of Massive multiple-input multiple-output (MIMO) systems. A closed-form uplink achievable data rate expression is derived considering imperfect channel state information (CSI) and hardware impairments. We formulate an optimization problem to maximize the sum data rate subject to a constraint on the total power consumption. A general power consumption model accounting for the level of hardware impairments is utilized. The optimization variables are the number of base station (BS) antennas and the level of impairments per BS antenna. The resolution of the analog-to-digital converter (ADC) is a primary source of such impairments. The results show the trade-off between the number of BS antennas and the level of hardware impairments, which is important for practical hardware design. Moreover, the maximum power consumption can be tuned to achieve maximum energy efficiency (EE). Numerical results suggest that the optimal level of hardware impairments yields ADCs of 4 to 5 quantization bits.

  • 7.
    Verenzuela, Daniel
    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.
    Matthaiou, Michail
    Institute of Electronics, Communications and Information Technology (ECIT), Queen’s University Belfast, .
    Per-antenna hardware optimization and mixed resolution ADCs in uplink massive MIMO2017In: Conference Record of The Fifty-FirstAsilomar Conference on Signals, Systems & Computers / [ed] Michael B. Matthews, IEEE conference proceedings, 2017, p. 27-31Conference paper (Refereed)
    Abstract [en]

    Massive multiple-input multiple-output (MIMO) is a key technology for next generation wireless networks that deploys many antennas at the base stations (BSs). This requires low-complexity hardware at each antenna branch that, in turn, increases distortions. This work studies the selection of per-antenna hardware quality in terms of analog-to-digital converters (ADCs) resolution. A new achievable spectral efficiency (SE) expression is derived and majorization theory is used to analyze the order preserving properties of the SE and the power consumption with respect to the per-antenna ADC resolutions. That is, given a fixed sum of ADC resolutions across the antenna array, is it preferable to use an equal-ADC over a mixed-ADC approach? The results show that having equal-resolution ADCs across the antenna array maximizes the SE and minimizes the power consumption.

  • 8.
    Verenzuela, Daniel
    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.
    Sanguinetti, Luca
    Dipartimento di Ingegneria dell’Informazione, University of Pisa, Pisa, Italy; Large Networks and System Group (LANEAS), CentraleSupélec, Université Paris-Saclay, Gif-sur-Yvette, France.
    Joint UL and DL Spectral Efficiency Optimization of Superimposed Pilots in Massive MIMO2017In: Proceedings of 2017 IEEE Globecom Workshops (GC Wkshps), IEEE, 2017, p. 1-7Conference paper (Refereed)
    Abstract [en]

    The reuse of pilot sequences in a Massive MIMO system leads to pilot contamination, which reduces the channel estimation quality and adds coherent interference in the data transmission. A standard method to reduce pilot contamination, known as regular pilots (RPs), is to increase the pilot overhead and reuse pilots more sparsely in the network. Another approach, denoted as superimposed pilots (SPs), is to send a superposition of pilot and data symbols which allows the system to reuse pilots far more sparsely. This work performs a comparative analysis of RPs and SPs in Massive MIMO considering the joint spectral efficiency (SE) of the uplink (UL) and downlink (DL) communications. A rigorous DL lower bound on the capacity with SPs is derived and multiobjective optimization theory is used to compare the UL and DL SE between RPs and SPs. Numerical results indicate that RPs and SPs give comparable SE when both methods are optimized.

  • 9.
    Verenzuela, Daniel
    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.
    Sanguinetti, Luca
    University of Pisa, Pisa, Italy.
    Optimal Design of Wireless Networks for Broadband Access with Minimum Power Consumption2016In: 2016 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), IEEE Communications Society, 2016Conference paper (Refereed)
    Abstract [en]

    The continuous rise in wireless data traffic brings forth an increase in power consumption and static users constitute a large fraction of these traffic demands. This work focuses on designing cellular networks to deliver a given data rate per area and user, while minimizing the power consumption. In particular we are interested in optimizing the transmission power, density of access points (APs), number of AP antennas and number of users served in each cell. To this end, we consider a network model based on stochastic geometry and a detailed power consumption model to derive closed form expressions and obtain insights on the interplay of the aforementioned design parameters. The results show that, in contrast with previous works on optimal network design for energy efficiency, having exceedingly high AP density does not bring the most benefits in terms of power savings. Instead the AP density should be chosen according to the area data rate that we want to deliver. In addition numerical results show that the minimum power consumption is obtained in the Massive MIMO regime with many antennas and users per AP.

  • 10.
    Verenzuela, Daniel
    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.
    Sanguinetti, Luca
    Univ Pisa, Italy; Univ Paris Saclay, France.
    Spectral and Energy Efficiency of Superimposed Pilots in Uplink Massive MIMO2018In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 17, no 11, p. 7099-7115Article in journal (Refereed)
    Abstract [en]

    Next-generation wireless networks aim at providing substantial improvements in spectral efficiency (SE) and energy efficiency (EE). Massive MIMO has been proved to be a viable technology to achieve these goals by spatially multiplexing several users using many base station (BS) antennas. A potential limitation of massive MIMO in multicell systems is pilot contamination, which arises in the channel estimation process from the interference caused by reusing pilots in neighboring cells. A standard method to reduce pilot contamination, known as regular pilot (RP), is to adjust the length of pilot sequences while transmitting data and pilot symbols disjointly. An alternative method, called superimposed pilot (SP), sends a superposition of pilot and data symbols. This allows use of longer pilots which, in turn, reduces pilot contamination. We consider the uplink of a multicell massive MIMO network, with i.i.d. Rayleigh fading channels, using maximum ratio combining and compare RP and SP in terms of SE and EE. To this end, we derive rigorous closed-form achievable rates with SP under a practical random BS deployment. We prove that the reduction of pilot contamination with SP is outweighed by the additional coherent and non-coherent interference. Numerical results show that when both methods are optimized, RP achieves comparable SE and EE to SP in practical scenarios.

  • 11.
    Verenzuela, Daniel
    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.
    Sanguinetti, Luca
    Univ Pisa, Italy; Univ Paris Saclay, France.
    Spectral Efficiency of Superimposed Pilots in Uplink Massive MIMO Systems2017In: GLOBECOM 2017 - 2017 IEEE GLOBAL COMMUNICATIONS CONFERENCE, IEEE , 2017Conference paper (Refereed)
    Abstract [en]

    Massive multiple-input multiple-output (MIMO) is a viable technology to improve the spectral efficiency (SE) by spatially multiplexing several users. A potential limitation of Massive MIMO in multicell systems is pilot contamination, which arises from interference in the channel estimation due to the reuse of pilot sequences in neighboring cells. A standard method to reduce pilot contamination, referred to as regular pilot (RP), is to adjust the length of the pilot sequences while transmitting data and pilot symbols disjointly. Alternatively, the superimposed pilot (SP) method sends a superposition of pilot and data symbols, thereby allowing the use of longer pilots which can also reduce pilot contamination. This work considers the uplink of a general multicell Massive MIMO system with SP and maximum ratio combining and derives rigorous closed-form achievable rates, which are used to make comparisons with RP. Numerical results consider a realistic random base station deployment and show that with SP the reduction of pilot contamination is outweighed by the additional coherent and non-coherent interference from the data transmission. Moreover, it turns out that, when the pilot length is optimized, RP provides comparable SE as with SP.

  • 12.
    Verenzuela, Daniel
    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.
    Wang, Xiaojie
    University of Stuttgart, Stuttgart, Germany.
    Arnold, Maximilian
    University of Stuttgart, Stuttgart, Germany.
    Brink, Stephan ten
    University of Stuttgart, Stuttgart, Germany.
    Massive-MIMO Iterative Channel Estimation and Decoding (MICED) in the Uplink2019In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, p. 1-1Article in journal (Refereed)
    Abstract [en]

    Massive MIMO uses a large number of antennas to increase the spectral efficiency (SE) through spatial multiplexing of users, which requires accurate channel state information. It is often assumed that regular pilots (RP), where a fraction of the time-frequency resources is reserved for pilots, suffices to provide high SE. However, the SE is limited by the pilot overhead and pilot contamination. An alternative is superimposed pilots (SP) where all resources are used for pilots and data. This removes the pilot overhead and reduces pilot contamination by using longer pilots. However, SP suffers from data interference that reduces the SE gains. This paper proposes the Massive-MIMO Iterative Channel Estimation and Decoding (MICED) algorithm where partially decoded data is used as side-information to improve the channel estimation and increase SE. We show that users with precise data estimates can help users with poor data estimates to decode. Numerical results with QPSK modulation and LDPC codes show that the MICED algorithm increases the SE and reduces the block-error-rate with RP and SP compared to conventional methods. The MICED algorithm with SP delivers the highest SE and it is especially effective in scenarios with short coherence blocks like high mobility or high frequencies.

  • 13.
    Verenzuela, Daniel
    et al.
    Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, Faculty of Science & Engineering.
    Miao, Guowang
    KTH Royal Institute Technology, Sweden; Freelinguist Com, Sweden.
    Scalable D2D Communications for Frequency Reuse 1 in 5G2017In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 16, no 6, p. 3435-3447Article in journal (Refereed)
    Abstract [en]

    Proximity-based applications are becoming fast growing markets suggesting that device-to-device (D2D) communications is becoming an essential part of the future mobile data networks. We propose scalable admission and power control methods for D2D communications underlay cellular networks to increase the reuse of frequency resources and thus network capacity while maintaining QoS to all users. In practice, as D2D communications will generate a new layer of interference, it is essential to take D2D interference into account in inter-cell interference coordination for multi-cell communications. The aim of the proposed methods is to maximize the number of D2D links under QoS constraints, therefore maximizing network frequency reuse in a practical 5G multi-cell environment. Different schemes are designed for applications that have different levels of complexity and availability of channel state information. Numerical results show that by using D2D and the proposed multi-cell interference coordination and low power transmission method, the network spectral efficiency can be increased by as much as ten times, while low outage probability can be assured to provide QoS for all users.

1 - 13 of 13
CiteExportLink to result list
Permanent link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf