Diversity Combining With Imperfect Channel Estimation

Abstract

We propose an iterative extension of the Bell Laboratory Layered Space-Time (BLAST) algorithm and its variant VBLAST. A characteristic feature of the BLAST-type algorithm is that symbol de- cisions with low reliability are fed back to decode other symbols. Both performance analysis based on Gaussian approximation of residual inter- ference and simulation results demonstrate that error propagation due to unreliable decision feedback can severely limit system performance. The extended algorithm exploits inherent signal diversity in BLAST to mitigate residual interference, thus overcoming the performance bottleneck due to error propagation. It yields an impressive performance gain over BLAST. In particular, the extension of BLAST with zero-forcing interference nulling (EXT-ZF-BLAST) admits a simple QR implementation and exhibits excellent performance with low complexity. Abstract—An optimal diversity-combining technique is investigated for a multipath Rayleigh fading channel with imperfect channel state informa- tion at the receiver. Applying minimum mean-square error channel esti- mation, the channel state can be decomposed into the channel estimator spanned by channel observation and the estimation error orthogonal to channel observation. The optimal combining weight is obtained from first principle of maximum a posteriori detection, taking into consideration the imperfect channel estimation. The bit-error performance using the optimal diversity combining is derived and compared with that of the suboptimal application of maximal ratio combining. Numerical results are presented for specific channel models and estimation methods to illustrate the com- bined effect of channel estimation and detection on bit-error rate perfor- mance.