On error rate performance of multi-cell massive MIMO systems with linear receivers

Abstract For an uplink of multi-cell multiuser (MU) Multiple-Input, Multiple-Output (MIMO) system, where each cell has a Base Station (BS) with M antennas and K users with single antenna, the Zero-Forcing (ZF) decoder and the Minimal Mean-Square Error (MMSE) decoder are considered. Upper bounds, lower bounds on Pair-wise Error Probability (PEP) of these decoders are derived. Moreover, analytic expressions of approximations on PEP are given. These show that, if the BS knows Channel State Information (CSI) in its own cell only and does not have CSI in other cells, error floors will occur even when Signal-to-Noise Ratio (SNR) goes to infinity for both the ZF decoder and the MMSE decoder, while these error floors disappear when M goes to large. All theoretical results above are confirmed by simulations. Especially, the approximations of PEP match up with simulation results very well.

[1]  Erik G. Larsson,et al.  Uplink Performance Analysis of Multicell MU-SIMO Systems With ZF Receivers , 2012, IEEE Transactions on Vehicular Technology.

[2]  Yi Jiang,et al.  Performance Analysis of ZF and MMSE Equalizers for MIMO Systems: An In-Depth Study of the High SNR Regime , 2011, IEEE Transactions on Information Theory.

[3]  Sergio Verdú,et al.  Asymptotic normality of linear multiuser receiver outputs , 2002, IEEE Trans. Inf. Theory.

[4]  Erik G. Larsson,et al.  Energy and Spectral Efficiency of Very Large Multiuser MIMO Systems , 2011, IEEE Transactions on Communications.

[5]  Michail Matthaiou,et al.  Sum Rate Analysis of ZF Receivers in Distributed MIMO Systems , 2013, IEEE Journal on Selected Areas in Communications.

[6]  Shlomo Shamai,et al.  Spectral Efficiency of CDMA with Random Spreading , 1999, IEEE Trans. Inf. Theory.

[7]  Thomas L. Marzetta,et al.  Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas , 2010, IEEE Transactions on Wireless Communications.

[8]  Hyuncheol Park,et al.  Performance Analysis of MIMO System with Linear MMSE Receiver , 2008, IEEE Transactions on Wireless Communications.

[9]  David Tse,et al.  Linear multiuser receivers in random environments , 2000, IEEE Trans. Inf. Theory.

[10]  John M. Cioffi,et al.  On the distribution of SINR for the MMSE MIMO receiver and performance analysis , 2006, IEEE Transactions on Information Theory.

[11]  Mérouane Debbah,et al.  Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need? , 2013, IEEE Journal on Selected Areas in Communications.

[12]  H. Vincent Poor,et al.  Probability of error in MMSE multiuser detection , 1997, IEEE Trans. Inf. Theory.

[13]  David Tse,et al.  Linear Multiuser Receivers: Effective Interference, Effective Bandwidth and User Capacity , 1999, IEEE Trans. Inf. Theory.

[14]  Sergio Verdu,et al.  Multiuser Detection , 1998 .

[15]  M. V. Clark,et al.  Theoretical reliability of MMSE linear diversity combining in Rayleigh-fading additive interference channels , 1998, IEEE Trans. Commun..

[16]  Xuzheng Lin,et al.  New Exponential Lower Bounds on the Gaussian Q-Function via Jensen's Inequality , 2011, 2011 IEEE 73rd Vehicular Technology Conference (VTC Spring).

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

[18]  Edwin K. P. Chong,et al.  Output MAI distributions of linear MMSE multiuser receivers in DS-CDMA systems , 2001, IEEE Trans. Inf. Theory.