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Massive MIMO: Fundamentals and System Designs
Linköping University, Department of Electrical Engineering, Communication Systems. Linköping University, The Institute of Technology.
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The last ten years have seen a massive growth in the number of connected wireless devices. Billions of devices are connected and managed by wireless networks. At the same time, each device needs a high throughput to support applications such as voice, real-time video, movies, and games. Demands for wireless throughput and the number of wireless devices will always increase. In addition, there is a growing concern about energy consumption of wireless communication systems. Thus, future wireless systems have to satisfy three main requirements: i) having a high throughput; ii) simultaneously serving many users; and iii) having less energy consumption. Massive multiple-input multiple-output (MIMO) technology, where a base station (BS) equipped with very large number of antennas (collocated or distributed) serves many users in the same time-frequency resource,  can meet the above requirements, and hence, it is a promising candidate technology for next generations of wireless systems. With massive antenna arrays at the BS, for most propagation environments, the channels become favorable, i.e., the channel vectors between the users and the BS are (nearly) pairwisely orthogonal, and hence, linear processing is nearly optimal. A huge throughput and energy efficiency can be achieved due to the multiplexing gain and the array gain. In particular, with a simple power control scheme, Massive MIMO can offer uniformly good service for all users. In this dissertation, we focus on the performance of Massive MIMO. The dissertation consists of two main parts: fundamentals and system designs of Massive MIMO.

In the first part, we focus on fundamental limits of the system performance under practical constraints such as low complexity processing, limited length of each coherence interval, intercell interference, and finite-dimensional channels. We first study the potential for power savings of the Massive MIMO uplink with maximum-ratio combining (MRC), zero-forcing, and minimum mean-square error receivers, under perfect and imperfect channels. The energy and spectral efficiency tradeoff is investigated. Secondly, we consider a physical channel model where the angular domain is divided into a finite number of distinct directions. A lower bound on the capacity is derived, and the effect of pilot contamination in this finite-dimensional channel model is analyzed. Finally, some aspects of favorable propagation in Massive MIMO under Rayleigh fading and line-of-sight (LoS) channels are investigated. We show that both Rayleigh fading and LoS environments offer favorable propagation.

In the second part, based on the fundamental analysis in the first part, we propose some system designs for Massive MIMO. The acquisition of channel state information (CSI) is very importantin Massive MIMO. Typically, the channels are estimated at the BS through uplink training. Owing to the limited length of the coherence interval, the system performance is limited by pilot contamination. To reduce the pilot contamination effect, we propose an eigenvalue-decomposition-based scheme to estimate the channel directly from the received data. The proposed scheme results in better performance compared with the conventional training schemes due to the reduced pilot contamination. Another important issue of CSI acquisition in Massive MIMO is how to acquire CSI at the users. To address this issue, we propose two channel estimation schemes at the users: i) a downlink "beamforming training" scheme, and ii) a method for blind estimation of the effective downlink channel gains. In both schemes, the channel estimation overhead is independent of the number of BS antennas. We also derive the optimal pilot and data powers as well as the training duration allocation to maximize the sum spectral efficiency of the Massive MIMO uplink with MRC receivers, for a given total energy budget spent in a coherence interval. Finally, applications of Massive MIMO in relay channels are proposed and analyzed. Specifically, we consider multipair relaying systems where many sources simultaneously communicate with many destinations in the same time-frequency resource with the help of a massive MIMO relay. A massive MIMO relay is equipped with many collocated or distributed antennas. We consider different duplexing modes (full-duplex and half-duplex) and different relaying protocols (amplify-and-forward, decode-and-forward, two-way relaying, and one-way relaying) at the relay. The potential benefits of massive MIMO technology in these relaying systems are explored in terms of spectral efficiency and power efficiency.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2015. , 45 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1642
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:liu:diva-112780DOI: 10.3384/lic.diva-112780ISBN: 978-91-7519-147-8 (print)OAI: oai:DiVA.org:liu-112780DiVA: diva2:772015
Public defence
2015-03-06, Signalen, Hus B, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2015-01-16 Created: 2014-12-15 Last updated: 2016-08-31Bibliographically approved
List of papers
1. Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems
Open this publication in new window or tab >>Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems
2013 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 61, no 4, 1436-1449 p.Article in journal (Refereed) Published
Abstract [en]

A multiplicity of autonomous terminals simultaneously transmits data streams to a compact array of antennas. The array uses imperfect channel-state information derived from transmitted pilots to extract the individual data streams. The power radiated by the terminals can be made inversely proportional to the square-root of the number of base station antennas with no reduction in performance. In contrast if perfect channel-state information were available the power could be made inversely proportional to the number of antennas. Lower capacity bounds for maximum-ratio combining (MRC), zero-forcing (ZF) and minimum mean-square error (MMSE) detection are derived. An MRC receiver normally performs worse than ZF and MMSE. However as power levels are reduced, the cross-talk introduced by the inferior maximum-ratio receiver eventually falls below the noise level and this simple receiver becomes a viable option. The tradeoff between the energy efficiency (as measured in bits/J) and spectral efficiency (as measured in bits/channel use/terminal) is quantified for a channel model that includes small-scale fading but not large-scale fading. It is shown that the use of moderately large antenna arrays can improve the spectral and energy efficiency with orders of magnitude compared to a single-antenna system.

National Category
Communication Systems Signal Processing
Identifiers
urn:nbn:se:liu:diva-85224 (URN)10.1109/TCOMM.2013.020413.110848 (DOI)000318998100022 ()
Available from: 2012-11-12 Created: 2012-11-12 Last updated: 2017-12-07
2. The Multicell Multiuser MIMO Uplink with Very Large Antenna Arrays and a Finite-Dimensional Channel
Open this publication in new window or tab >>The Multicell Multiuser MIMO Uplink with Very Large Antenna Arrays and a Finite-Dimensional Channel
2013 (English)In: IEEE Transactions on Communications, ISSN 0090-6778, E-ISSN 1558-0857, Vol. 61, no 6, 2350-2361 p.Article in journal (Refereed) Published
Abstract [en]

We consider multicell multiuser MIMO systems with a very large number of antennas at the base station (BS). We assume that the channel is estimated by using uplink training. We further consider a physical channel model where the angular domain is separated into a finite number of distinct directions. We analyze the so-called pilot contamination effect discovered in previous work, and show that this effect persists under the finite-dimensional channel model that we consider. In particular, we consider a uniform array at the BS. For this scenario, we show that when the number of BS antennas goes to infinity, the system performance under a finite-dimensional channel model with P angular bins is the same as the performance under an uncorrelated channel model with P antennas. We further derive a lower bound on the achievable rate of uplink data transmission with a linear detector at theBS. We then specialize this lower bound to the cases of maximum-ratio combining (MRC) and zero-forcing (ZF) receivers, for a finite and an infinite number of BS antennas. Numerical results corroborate our analysis and show a comparison between the performances of MRC and ZF in terms of sum-rate.

Keyword
Finite-dimensional channel, multicell mutiuser MIMO, pilot contamination, very large MIMO systems
National Category
Communication Systems Signal Processing
Identifiers
urn:nbn:se:liu:diva-85223 (URN)10.1109/TCOMM.2013.032713.120408 (DOI)000321219100023 ()
Available from: 2013-04-04 Created: 2012-11-12 Last updated: 2017-12-06Bibliographically approved
3. Aspects of Favorable Propagation in Massive MIMO
Open this publication in new window or tab >>Aspects of Favorable Propagation in Massive MIMO
2014 (English)In: European Signal Processing Conference (EUSIPCO), EURASIP , 2014, 76-80 p.Conference paper, Published paper (Refereed)
Abstract [en]

Favorable propagation, dened as mutual orthogonality among the vector-valued channels to the terminals, is one of the key properties of the radio channel that is exploited in Massive MIMO. However, there has been little work that studies this topic in detail. In this paper, we first show that favorable propagation offers the most desirable scenario in terms of maximizing the sum-capacity. One useful proxy for whether propagation is favorable or not is the channel condition number. However, this proxy is not good for the case where the norms of the channel vectors are not equal. For this case, to evaluate how favorable the propagation oered by the channel is, we propose a distance from favorable propagation measure, which is the gap between the sum-capacity and the maximum capacity obtained under favorable propagation. Secondly, we examine how favorable the channels can be for two extreme scenarios: i.i.d. Rayleigh fading and uniform random line-of-sight(UR-LoS). Both environments offer (nearly) favorable propagation. Furthermore, to analyze the UR-LoS model, we propose an urns-and-balls model. This model is simple and explains the singular value spread characteristic of the UR-LoS model well.

Place, publisher, year, edition, pages
EURASIP, 2014
Series
Proceedings of the European Signal Processing Conference, ISSN 2076-1465
National Category
Communication Systems Signal Processing
Identifiers
urn:nbn:se:liu:diva-112757 (URN)2-s2.0-84911883360 (Scopus ID)978-099286261-9 (ISBN)
Conference
22nd European Signal Processing Conference, EUSIPCO 2014
Available from: 2014-12-15 Created: 2014-12-15 Last updated: 2016-09-14
4. EVD-based Channel Estimations for Multicell Multiuser MIMO with Very Large Antenna Arrays
Open this publication in new window or tab >>EVD-based Channel Estimations for Multicell Multiuser MIMO with Very Large Antenna Arrays
2012 (English)In: Proceedings of the IEEE International Conference on Acoustics, Speed and Signal Processing (ICASSP), IEEE , 2012, 3249-3252 p.Conference paper, Published paper (Refereed)
Abstract [en]

This paper considers multicell multiuser MIMO systems with verylarge antenna arrays at the base station. We propose an eigenvalue-decomposition-based approach to channel estimation, that estimates the channel blindly from the received data. The approach exploits the asymptotic orthogonality of the channel vectors in very large MIMO systems. We show that the channel to each user can be estimated from the covariance matrix of the received signals, up to a remaining scalar multiplicative ambiguity. A short training sequence is required to resolve this ambiguity. Furthermore, to improve the performance of our approach, we combine it with the iterative least-square with projection (ILSP) algorithm. Numerical results verify the effectiveness of our channel estimation approach.

Place, publisher, year, edition, pages
IEEE, 2012
Series
Acoustics, Speech and Signal Processing (ICASSP), ISSN 1520-6149
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-74084 (URN)10.1109/ICASSP.2012.6288608 (DOI)000312381403081 ()978-1-4673-0045-2 (ISBN)978-1-4673-0044-5 (ISBN)
Conference
IEEE International Conference on Acoustics, Speed and Signal Processing (ICASSP, March 25-30, Kyoto, Japan
Available from: 2012-01-18 Created: 2012-01-18 Last updated: 2016-08-31Bibliographically approved
5. Massive MU-MIMO Downlink TDD Systems with Linear Precodingand Downlink Pilots
Open this publication in new window or tab >>Massive MU-MIMO Downlink TDD Systems with Linear Precodingand Downlink Pilots
2013 (English)In: 51st Annual Allerton Conference on Communication, Control, and Computing (Allerton), 2013, IEEE , 2013, 293-298 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider a massive MU-MIMO downlink time-division duplex system where a base station (BS) equipped with many antennas serves several single-antenna users in the same time-frequency resource. We assume that the BS uses linear precoding for the transmission. To reliably decode the signals transmitted from the BS, each user should have an estimate of its channel. In this work, we consider an efficient channel estimation scheme to acquire CSI at each user, called beamforming training scheme. With the beamforming training scheme, the BS precodes the pilot sequences and forwards to all users. Then, based on the received pilots, each user uses minimum mean-square error channel estimation to estimate the effective channel gains. The channel estimation overhead of this scheme does not depend on the number of BS antennas, and is only proportional to the number of users. We then derive a lower bound on the capacity for maximum-ratio transmission and zero-forcing precoding techniques which enables us to evaluate the spectral efficiency taking into account the spectral eciency loss associated with the transmission of the downlink pilots. Comparing with previous work where each user uses only the statistical channel properties to decode the transmitted signals, we see that the proposed beamforming training scheme is preferable for moderate and low-mobility environments.

Place, publisher, year, edition, pages
IEEE, 2013
National Category
Communication Systems Signal Processing
Identifiers
urn:nbn:se:liu:diva-112758 (URN)10.1109/Allerton.2013.6736537 (DOI)978-1-4799-3409-6 (ISBN)
Conference
51st Annual Allerton Conference on Communication, Control, and Computing (Allerton), October 2-4, Monticello, Illinois, USA
Available from: 2014-12-15 Created: 2014-12-15 Last updated: 2016-08-31Bibliographically approved
6. Blind estimation of effective downlink channel gains in massive MIMO
Open this publication in new window or tab >>Blind estimation of effective downlink channel gains in massive MIMO
2015 (English)In: 2015 IEEE International Conference on Acoustics, Speech, and Signal Processing, Proceedings, IEEE , 2015, 2919-2923 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider the massive MIMO downlink with time-division duplex (TDD) operation and conjugate beamforming transmission. To reliably decode the desired signals, the users need to know the effective channel gain. In this paper, we propose a blind channel estimation method which can be applied at the users and which does not require any downlink pilots. We show that our proposed schemecan substantially outperform the case where each user has only statistical channel knowledge, and that the difference in performance is particularly large in certain types of channel, most notably keyhole channels. Compared to schemes that rely on downlink pilots(e.g., [1]), our proposed scheme yields more accurate channel estimates for a wide range of signal-to-noise ratios and avoid spending time-frequency resources on pilots.

Place, publisher, year, edition, pages
IEEE, 2015
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keyword
Blind channel estimation, downlink, massive MIMO, time-division duplex
National Category
Communication Systems Telecommunications
Identifiers
urn:nbn:se:liu:diva-129072 (URN)10.1109/ICASSP.2015.7178505 (DOI)000368452403012 ()978-1-4673-6997-8 (ISBN)
Conference
40th IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)
Available from: 2016-06-10 Created: 2016-06-10 Last updated: 2016-08-31Bibliographically approved
7. Massive MIMO with Optimal Power and Training Duration Allocation
Open this publication in new window or tab >>Massive MIMO with Optimal Power and Training Duration Allocation
2014 (English)In: IEEE Wireless Communications Letters, ISSN 2162-2337, E-ISSN 2162-2345, Vol. 3, no 6, 605-608 p.Article in journal (Refereed) Published
Abstract [en]

We consider the uplink of massive multicell multiple-input multiple-output systems, where the base stations (BSs), equipped with massive arrays, serve simultaneously several terminals in the same frequency band. We assume that the BS estimates the channel from uplink training, and then uses the maximum ratio combining technique to detect the signals transmitted from all terminals in its own cell. We propose an optimal resource allocation scheme which jointly selects the training duration,training signal power, and data signal power in order to maximize the sum spectral efficiency, for a given total energy budget spent in a coherence interval. Numerical results verify the benets of the optimal resource allocation scheme. Furthermore, we show that more training signal power should be used at low signal-to-noise ratio(SNRs), and vice versa at high SNRs. Interestingly, for the entire SNR regime, the optimal training duration is equal to the number of terminals.

Place, publisher, year, edition, pages
IEEE, 2014
Keyword
Channel estimation, MIMO, Power distribution, Resource management, Signal to noise ratio, Uplink
National Category
Communication Systems Signal Processing
Identifiers
urn:nbn:se:liu:diva-112760 (URN)10.1109/LWC.2014.2359220 (DOI)000209681700015 ()2-s2.0-84919821841 (Scopus ID)
Available from: 2014-12-15 Created: 2014-12-15 Last updated: 2017-12-05Bibliographically approved
8. Large-Scale Multipair Two-Way Relay Networks with Distributed AF Beamforming
Open this publication in new window or tab >>Large-Scale Multipair Two-Way Relay Networks with Distributed AF Beamforming
2013 (English)In: IEEE Communications Letters, ISSN 1089-7798, E-ISSN 1558-2558, Vol. 17, no 12, 1-4 p.Article in journal (Refereed) Published
Abstract [en]

We consider a multipair two-way relay network where multiplecommunication pairs simultaneously exchange information with the helpof multiple relay nodes. All nodes are equipped with a single antennaand channel state information is available only at the relay nodes. Each relay uses very simplesignal processing in a distributed manner, called distributed amplify-and-forward (AF)  relaying. A closed-form expression for the achievable rate is  derived. We show that the distributed AF scheme outperforms conventional orthogonal relaying. When the number of relay nodes is large, the distributed AF relaying scheme can achieve the capacity scaling given by the cut-set upper bound. Furthermore, when the number of relay nodes grows large, the transmit powers of each terminal and of the relay can be made inversely proportional to the number of relay nodes while maintaining a given quality-of-service. If the transmit power of each terminal is kept fixed, the transmit power of each relay node can be scaled down inversely proportional to the square of the number of relays.

Place, publisher, year, edition, pages
IEEE Press, 2013
National Category
Communication Systems Signal Processing Telecommunications
Identifiers
urn:nbn:se:liu:diva-98122 (URN)10.1109/LCOMM.2013.102213.131813 (DOI)000329528200021 ()
Available from: 2013-09-30 Created: 2013-09-30 Last updated: 2017-12-06
9. Spectral Efficiency of the Multipair Two-Way Relay Channel with Massive Arrays
Open this publication in new window or tab >>Spectral Efficiency of the Multipair Two-Way Relay Channel with Massive Arrays
2013 (English)In: Asilomar Conference on Signals, Systems and Computers, 2013, IEEE , 2013, 275-279 p.Conference paper, Published paper (Refereed)
Abstract [en]

We consider a multipair two-way relay channel where multiple communication pairs share the same time-frequency resource and a common relay node. We assume that all users have a single antenna, while the relay node is equipped with a very large antenna array. We consider two transmission schemes: (I) separate-training zero-forcing (ZF) and (II) a new proposed coupled-training ZF. For both schemes, the channels are estimated at the relay by using training sequences, assuming time-division duplex operation. The relay processes the received signals using ZF. With the separate-training ZF, the channels from all users are estimated separately. By contrast, with the coupled-training ZF, the relay estimates the sum of the channels from two users of a given communication pair. This reduces the amount of resources spent in the training phase. Self-interference reduction is also proposed for these schemes. When the number of relay antennas grows large, the effects of interpair interference and self-interference can be neglected. The transmit power of each user and of the relay can be made inversely proportional to the square root of the number of relay antennas while maintaining a given quality-of-service. We derive a lower bound on the capacity which enables us to evaluate the spectral efficiency. The coupled-training ZF scheme is preferable for the high-mobility environment, while the separate-training ZF scheme is preferable for the low-mobility environment.

Place, publisher, year, edition, pages
IEEE, 2013
Series
ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS, ISSN 1058-6393
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:liu:diva-111472 (URN)000341772900049 ()978-1-4799-2388-5 (ISBN)
Conference
47th Asilomar Conference on Signals, Systems and Computers, November 3-6, Pacific Grove, Califronia, USA
Available from: 2014-10-17 Created: 2014-10-17 Last updated: 2016-08-31Bibliographically approved
10. Multipair Full-Duplex Relaying with Massive Arrays and Linear Processing
Open this publication in new window or tab >>Multipair Full-Duplex Relaying with Massive Arrays and Linear Processing
2014 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 32, no 9, 1721-1737 p.Article in journal (Refereed) Published
Abstract [en]

We consider a multipair decode-and-forward relay channel, where multiple sources transmit simultaneously their signals to multiple destinations with the help of a full-duplex relay station. We assume that the relay station is equipped with massive arrays, while all sources and destinations have a single antenna. The relay station uses channel estimates obtained from received pilots and zero-forcing (ZF) or maximum-ratio combining/maximum-ratio transmission (MRC/MRT) to process the signals. To signicantly reduce the loop interference effect, we propose two techniques: i) using a massive receive antenna array; or ii) using a massive transmit antenna array together with very low transmit power at the relay station. We derive an exact achievable rate expression in closed-form for MRC/MRT processing and an analytical approximation of the achievable rate for ZF processing. This approximation is very tight, particularly for a large number of relay station antennas. These closed-form expressions enable us to determine the regions where the full-duplex mode outperforms the half-duplex mode, as well as to design an optimal power allocation scheme. This optimal power allocation scheme aims to maximize the energy efficiency for a given sum spectral efficiency and under peak power constraints at the relay station and sources. Numerical results verify the effectiveness of the optimal power allocation scheme. Furthermore, we show that, by doubling the number of transmit/receive antennas at the relay station, the transmit power of each source and of the relay station can be reduced by 1.5 dB if the pilot power is equal to the signal power, and by 3 dB if the pilot power is kept fixed, while maintaining a given quality of service.

Place, publisher, year, edition, pages
IEEE: , 2014
National Category
Communication Systems Signal Processing
Identifiers
urn:nbn:se:liu:diva-112761 (URN)10.1109/JSAC.2014.2330091 (DOI)000346043400009 ()
Available from: 2014-12-15 Created: 2014-12-15 Last updated: 2017-12-05

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