Effective SINR Computation for Maximum Likelihood Detector in MIMO Spatial Multiplexing Systems

This paper studies the computation of post-processing signal-to-interference plus noise ratio (SINR) for maximum likelihood detector (MLD) in multiple-input and multiple output (MIMO)-orthogonal frequency division multiplexing (OFDM) spatial multiplexing systems. We derive an effective post-MLD SINR for each spatial stream, which is computed as post minimum mean-squared error (MMSE) SINR plus gain factor, where the gain factor is adaptively computed based on the instantaneous channel and modulation format of interfering streams. The post-MLD SINR is then applied to modulation and coding scheme (MCS) selection in adaptive modulation and coding. Simulation results show that the MCS selection using proposed post-MLD SINR can achieve throughput performance close to that of the optimum approach, and considerable gain can be achieved over linear-MMSE receiver.

[1]  Stephan ten Brink,et al.  Achieving near-capacity on a multiple-antenna channel , 2003, IEEE Trans. Commun..

[2]  Tricia J. Willink,et al.  Iterative tree search detection for MIMO wireless systems , 2005, IEEE Transactions on Communications.

[3]  Magnus Almgren,et al.  A fading-insensitive performance metric for a unified link quality model , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..

[4]  Kyeong Jin Kim,et al.  Joint channel estimation and data detection algorithms for MIMO-OFDM systems , 2002, Conference Record of the Thirty-Sixth Asilomar Conference on Signals, Systems and Computers, 2002..

[5]  Y.L.C. de Jong,et al.  Iterative tree search detection for MIMO wireless systems , 2002, Proceedings IEEE 56th Vehicular Technology Conference.

[6]  John G. Proakis,et al.  Digital Communications , 1983 .

[7]  R. V. Nee,et al.  Maximum likelihood decoding in a space division multiplexing system , 2000, VTC2000-Spring. 2000 IEEE 51st Vehicular Technology Conference Proceedings (Cat. No.00CH37026).

[8]  Joseph Jean Boutros,et al.  Accurate Approximation of QAM Error Probability on Quasi-Static MIMO Channels and Its Application to Adaptive Modulation , 2007, IEEE Transactions on Information Theory.