Diversity analysis and design of space-time multiblock codes for MIMO systems equipped with linear MMSE receivers

  • Authors:

  • Jing Liu;Timothy N. Davidson;K. Max Wong

  • Affiliations:

  • Siemens Canada, Peterborough, ON, Canada and Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada;Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada;Department of Electrical and Computer Engineering, McMaster University, Hamilton, ON, Canada

  • Venue:
  • IEEE Transactions on Information Theory
  • Year:
  • 2010

Quantified Score

Hi-index 754.84

Visualization

Abstract

This paper addresses the problem of designing optimum full-symbol-rate linear space-time block codes (STBC) for a multi-input multi-output (MIMO) communication system with M transmitter and N ≥ M receiver antennas and a linear minimum mean square error (MMSE) receiver. By analyzing the detection error probability expression for the optimized STBC, it is shown that for QAM signaling, the maximum diversity gain for such a system is N - M + 1. The minimum probability of error STBC design is then extended to systems in which the transmission spans L independent realizations from a block fading channel model, and a (multiblock) linear MMSE receiver is employed. Necessary and sufficient conditions for the optimality of the code are obtained, and a systematic design method for generating codes that satisfy these conditions is presented. The detection error probability and diversity gain of this optimized linear multiblock transceiver are analyzed. It is proved that the error probability decreases with L, and it is shown numerically that the diversity gain increases with L. Thus, if the corresponding latency can be accommodated, for sufficiently large L an optimally designed multiblock system with a linear receiver can exploit the temporal diversity provided by the block-fading channel and achieve higher diversity gain than that of any single-block system of the same symbol rate with a maximum likelihood (ML) receiver. The optimized multiblock linear system achieves this diversity at a substantially lower computational cost. In fact, the structure of the optimal codes can be exploited to significantly reduce the cost of the multiblock linear receiver.