Massive MIMO With Nonlinear Precoding: Large-System Analysis

In this paper, we consider time-domain vector perturbation (TDVP) in a large-system limit when channel state information (CSI) is imperfect due to pilot contamination, and we derive the system's achievable sum rate per cell. We use random matrix methods to avoid time-consuming Monte Carlo simulations. Numerical results show that, in general, linear precoding ensures a higher sum rate than TDVP in the massive multiple-input-multiple-output (MIMO) regime.

[1]  Antonia Maria Tulino,et al.  Network MIMO With Linear Zero-Forcing Beamforming: Large System Analysis, Impact of Channel Estimation, and Reduced-Complexity Scheduling , 2010, IEEE Transactions on Information Theory.

[2]  Uri Erez,et al.  Achieving 1/2 log (1+SNR) on the AWGN channel with lattice encoding and decoding , 2004, IEEE Transactions on Information Theory.

[3]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[4]  Antonia Maria Tulino,et al.  Random Matrix Theory and Wireless Communications , 2004, Found. Trends Commun. Inf. Theory.

[5]  Shlomo Shamai,et al.  On Vector Perturbation Precoding for the MIMO Gaussian Broadcast Channel , 2015, IEEE Transactions on Information Theory.

[6]  H. Miyakawa,et al.  Matched-Transmission Technique for Channels With Intersymbol Interference , 1972, IEEE Trans. Commun..

[7]  Erik G. Larsson,et al.  Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays , 2012, IEEE Signal Process. Mag..

[8]  Witold A. Krzymien,et al.  Vector Perturbation Precoding for Network MIMO: Sum Rate, Fair User Scheduling, and Impact of Backhaul Delay , 2012, IEEE Transactions on Vehicular Technology.

[9]  A. Lee Swindlehurst,et al.  A vector-perturbation technique for near-capacity multiantenna multiuser communication-part II: perturbation , 2005, IEEE Transactions on Communications.

[10]  Sean A. Ramprashad,et al.  Achieving "Massive MIMO" Spectral Efficiency with a Not-so-Large Number of Antennas , 2011, IEEE Transactions on Wireless Communications.

[11]  M. Tomlinson.  New automatic equaliser employing modulo arithmetic , 1971 .

[12]  Ralf R. Müller,et al.  Vector Precoding for Wireless MIMO Systems: A Replica Analysis , 2007, ArXiv.

[13]  Ralf R. Müller,et al.  Vector Precoding for Wireless MIMO Systems and its Replica Analysis , 2007, IEEE Journal on Selected Areas in Communications.

[14]  Shlomo Shamai,et al.  On the achievable throughput of a multiantenna Gaussian broadcast channel , 2003, IEEE Transactions on Information Theory.

[15]  Daniel J. Ryan,et al.  Sum rates, rate allocation, and user scheduling for multi-user MIMO vector perturbation precoding , 2010, IEEE Transactions on Wireless Communications.

[16]  Shlomo Shamai,et al.  The Capacity Region of the Gaussian Multiple-Input Multiple-Output Broadcast Channel , 2006, IEEE Transactions on Information Theory.

[17]  Giuseppe Caire,et al.  On achievable rates in a multi-antenna broadcast downlink , 2000 .