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On joint ML detection and decoding for linear block codes

Vikalo, Haris and Hassibi, Babak (2003) On joint ML detection and decoding for linear block codes. In: IEEE International Symposium on Information Theory, 2003. Proceedings. IEEE , Piscataway, NJ, p. 275. ISBN 0-7803-7728-1.

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We consider joint maximum-likelihood (ML) detection and decoding in multiple-input multiple-output (MIMO) systems. The information data is encoded by a linear block error-correcting code and then transmitted across the MIMO channel in AWGN. Geometrically, the transmitted symbol is a point in a high-dimensional lattice. The received symbol is the lattice point perturbed by an additive noise. The joint detection and decoding problem is equivalent to the search for the closest lattice point that is an admissible codeword. We propose an algorithm which performs a search constrained by a sphere centered at the observed point. The radius of the sphere is determined according to the statistics of the noise. Thus the computational complexity of the algorithm is a random variable. We quantify it by means of its first moment which, for binary codes, we And analytically. The expected complexity of the proposed algorithm is polynomial in the length of the uncoded information word over a wide range of SNRs.

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Additional Information:© 2003 IEEE. This work was supported in part by the National Science Foundation under grant no. CCR-0133818, by the Office of Naval Research under grant no. N00014-02-1-0578, and by Caltech's Lee Center for Advanced Networking.
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Office of Naval Research (ONR)N00014-02-1-0578
Caltech Lee Center for Advanced NetworkingUNSPECIFIED
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ID Code:55181
Deposited By: Shirley Slattery
Deposited On:09 Mar 2020 14:56
Last Modified:10 Nov 2021 20:42

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