Receiver performance-complexity tradeoff in LTE MU-MIMO transmission

Multi-user multiple-input and multiple-output (MU-MIMO) transmission scheme provides potential gain in terms of system capacity in spatial correlated scenarios and is considered as one of the key technologies in Long Term Evolution (LTE) systems. The goal of this paper is to gain insight into MU-MIMO detection concepts and their implementation aspects. Various receiver architectures are investigated and their performance are assessed through an advanced link-level simulator. The motivation to study the MU-MIMO detectors rises from the weakness of the co-channel interference-unaware single user detector, the conventional detector for single user MIMO transmission. The most essential problem of these conventional single user detectors in MU-MIMO is the failing to detect signals under the residual interference caused by co-scheduled user, which reduces the performance of the detector. Different practical scenarios have been considered in the evaluation process, namely low and high spatial correlation channels with real channel estimation and feedback delay. Our investigation has shown that single user receivers, such as maximum ratio combiner, show generally poor performance in MU-MIMO scenario and as such they should be neglected for practical implementation. Furthermore, we have shown that the interference rejection combiner achieves the best performance-complexity tradeoff and outperforms conventional single user detectors only with a small increase of computation efforts in signal processing.

[1]  Y. Lomnitz,et al.  Efficient maximum likelihood detector for MIMO systems with small number of streams , 2007 .

[2]  Andrew J. Viterbi,et al.  An Intuitive Justification and a Simplified Implementation of the MAP Decoder for Convolutional Codes , 1998, IEEE J. Sel. Areas Commun..

[3]  R. Heath,et al.  Limited feedback unitary precoding for spatial multiplexing systems , 2005, IEEE Transactions on Information Theory.

[4]  Gene H. Golub,et al.  Matrix computations (3rd ed.) , 1996 .

[5]  C. Carbonelli,et al.  Analytic performance evaluation of MIMO OFDM with pilot-aided channel estimation on doubly selective channels , 2010, Eur. Trans. Telecommun..

[6]  C. Spiegel,et al.  On MIMO with successive interference cancellation applied to UTRA LTE , 2008, 2008 3rd International Symposium on Communications, Control and Signal Processing.

[7]  Giuseppe Caire,et al.  Bit-Interleaved Coded Modulation , 2008, Found. Trends Commun. Inf. Theory.

[8]  P.A. Ranta,et al.  Interference rejection with a small antenna array at the mobile scattering environment , 1997, First IEEE Signal Processing Workshop on Signal Processing Advances in Wireless Communications.

[9]  Robert H. Halstead,et al.  Matrix Computations , 2011, Encyclopedia of Parallel Computing.

[10]  Raymond Knopp,et al.  Making multiuser MIMO work for LTE , 2010, 21st Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications.