Link-level performance estimation of ML receiver in MIMO-OFDM systems

Multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) technology is expected to provide theoretical capacity approaching performance if link adaptation techniques are employed. In this paper, we propose a new link-level estimation technique for maximum likelihood detector. The new proposed technique is able to decouple the modulation level and coding rate from each other in the modeling process. Both convolutional codes and Turbo codes are considered in this paper, with various coding rates and modulation schemes. It has been demonstrated through simulation that the proposed model provides satisfactory link performance prediction accuracy for various coding rates and modulation schemes.

[1]  Inkyu Lee,et al.  A New SNR Prediction Method for MIMO-OFDM Systems with Maximum Likelihood Detector , 2011, 2011 IEEE International Conference on Communications (ICC).

[2]  Angeliki Alexiou,et al.  Link performance models for system level simulations of broadband radio access systems , 2005, 2005 IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications.

[3]  Andrea J. Goldsmith,et al.  Adaptive coded modulation for fading channels , 1997, Proceedings of ICC'97 - International Conference on Communications.

[4]  Kyoung-Jae Lee,et al.  Link Performance Estimation Techniques for MIMO-OFDM Systems with Maximum Likelihood Receiver , 2012, IEEE Transactions on Wireless Communications.

[5]  Yiqing Zhou,et al.  Bit-Wise Exponential ESM (BE-ESM) Method for Accurate Link Level Performance Evaluation , 2009, 2009 IEEE International Conference on Communications.

[6]  Gerhard Bauch,et al.  Effective SINR Computation for Maximum Likelihood Detector in MIMO Spatial Multiplexing Systems , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[7]  W. T. Webb,et al.  Variable rate QAM for mobile radio , 1995, IEEE Trans. Commun..

[8]  Kenneth Stewart,et al.  Short Term Link Performance Modeling for ML Receivers with Mutual Information per Bit Metrics , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.