Title :
Coding-Assisted Blind MIMO Separation and Decoding
Author :
Zhao, Xu ; Davies, Mike
Author_Institution :
Sch. of Eng., Univ. of Edinburgh, Edinburgh, UK
Abstract :
Despite the widespread use of forward-error correcting (FEC) coding, most multiple-input-multiple-output (MIMO) blind channel-estimation techniques ignore its presence and instead make the simplifying assumption that the transmitted symbols are uncoded. However, FEC induces code structure in the transmitted sequence that can be exploited to improve blind MIMO channel estimates. In this paper, we exploit the iterative channel estimation based on a posteriori information for blind MIMO separation and decoding. Experiments show improvements that are achievable by exploiting the existence of coding structures and that our technique can approach the performance of a Bahl-Cocke-Jelinek-Raviv (BCJR) equalizer with perfect channel-state information in a reasonable signal-to-noise ratio (SNR) range. In addition, by splitting the FEC codeword over multiple blocks, the impact in performance of a bad-conditioned channel matrix can be kept at a reasonable level.
Keywords :
MIMO communication; blind source separation; channel estimation; decoding; forward error correction; iterative methods; Bahl-Cocke-Jelinek-Raviv equalizer; FEC codeword; a posteriori information; blind MIMO separation; coding; decoding; iterative channel estimation; multiple-input-multiple-output; signal-to-noise ratio; Blind equalizers; Channel estimation; Complexity theory; Decoding; Error correction; Forward error correction; Image coding; Independent component analysis; Iterative decoding; MIMO; Receiving antennas; Signal to noise ratio; Transmitting antennas; Blind channel estimation; Expectation–Maximization (EM) channel estimation; blind separation; independent component analysis (ICA); turbo equalization;
Journal_Title :
Vehicular Technology, IEEE Transactions on
DOI :
10.1109/TVT.2010.2066588