On Detection Issues in the SC-Based Uplink of a MU-MIMO System with a Large Number of BS Antennas

This paper deals with Single Carrier (SC)/Frequency Domain Equalization (FDE) within a Multi-User (MU)-Multi-Input Multi-Output (MIMO) system where a large number of Base Station (BS) antennas is adopted. In this context, we consider either a linear or a low-complexity iterative Decision-Feedback (DF) detection technique which does not require matrix inversion operations. We include a detailed evaluation of Bit Error Rate (BER) performances for uncoded 4-Quadrature Amplitude Modulation (4-QAM) schemes and a MUMIMO channel with uncorrelated Rayleigh fading. The accuracy of performance results obtained through selected semi-analytical simulation methods is assessed by means of parallel conventional Monte Carlo simulations; these results are discussed in detail, with the help of selected performance bounds. From our performance results, we conclude that a moderately large number of BS antennas is enough to closely approximate the Single-Input Multi-Output (SIMO) MatchedFilter Bound (MFB) performance, especially when using the low-complexity iterative DF technique. We also emphasize the achievable ”massive MIMO” effects, even for strongly reduced-complexity linear detection techniques, provided that the number of BS antennas is much higher than the number of antennas which are jointly employed in the terminals of the multiple autonomous users.

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

[2]  Hikmet Sari,et al.  An analysis of orthogonal frequency-division multiplexing for mobile radio applications , 1994, Proceedings of IEEE Vehicular Technology Conference (VTC).

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

[4]  Rui Dinis,et al.  A Turbo FDE Technique for Reduced-CP SC-Based Block Transmission Systems , 2007, IEEE Transactions on Communications.

[5]  E.G. Larsson,et al.  MIMO Detection Methods: How They Work [Lecture Notes] , 2009, IEEE Signal Processing Magazine.

[6]  E. Larsson,et al.  MIMO Detection Methods: How They Work , 2010 .

[7]  Rui Dinis,et al.  On frequency-domain equalization and diversity combining for broadband wireless communications , 2003, IEEE Trans. Commun..

[8]  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.

[9]  Gerard J. Foschini,et al.  Layered space-time architecture for wireless communication in a fading environment when using multi-element antennas , 1996, Bell Labs Technical Journal.

[10]  Robert W. Heath,et al.  Shifting the MIMO Paradigm , 2007, IEEE Signal Processing Magazine.

[11]  António Gusmão,et al.  Iterative Receiver Techniques for SC-FDMA Uplink Block Transmission: Design and Performance Evaluation , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[12]  Rui Dinis,et al.  A Class of Iterative FDE Techniques for Reduced-CP SC-Based Block Transmission , 2006 .

[13]  F. Schreckenbach,et al.  Iterative detection of MIMO signals with linear detectors , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[14]  R. Dinis,et al.  Comparison of two modulation choices for broadband wireless communications , 2000, VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026).

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