Performance analysis of linear codes under maximum-likelihood decoding: a tutorial
Communications and Information Theory
A Generalization of the Parallel Error Correcting Codes by Allowing Some Random Errors
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
A channel representation method for the study of hybrid retransmission-based error control
IEEE Transactions on Communications
Using the Bhattacharyya parameter for design and analysis of cooperative wireless systems
IEEE Transactions on Wireless Communications
Rateless coding for arbitrary channel mixtures with decoder channel state information
IEEE Transactions on Information Theory
Demultiplexer design for multi-edge type LDPC coded modulation
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
Performance bounds for nonbinary linear block codes over memoryless symmetric channels
IEEE Transactions on Information Theory
Optimization for fractional cooperation in multiple-source multiple-relay systems
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Adaptive coding and modulation for hybrid FSO/RF systems
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Proceedings of the Fifth ACM International Workshop on UnderWater Networks
LDPC code design considerations for non-uniform channels
IEEE Transactions on Communications
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We study the average error probability performance of binary linear code ensembles when each codeword is divided into J subcodewords with each being transmitted over one of J parallel channels. This model is widely accepted for a number of important practical channels and signaling schemes including block-fading channels, incremental redundancy retransmission schemes, and multicarrier communication techniques for frequency-selective channels. Our focus is on ensembles of good codes whose performance in a single channel model is characterized by a threshold behavior, e.g., turbo and low-density parity-check (LDPC) codes. For a given good code ensemble, we investigate reliable channel regions which ensure reliable communications over parallel channels under maximum-likelihood (ML) decoding. To construct reliable regions, we study a modifed 1961 Gallager bound for parallel channels. By allowing codeword bits to be randomly assigned to each component channel, the average parallel-channel Gallager bound is simplified to be a function of code weight enumerators and channel assignment rates. Special cases of this bound, average union-Bhattacharyya (UB), Shulman-Feder (SF), simplified-sphere (SS), and modified Shulman-Feder (MSF) parallel-channel bounds, allow for describing reliable channel regions using simple functions of channel and code spectrum parameters. Parameters describing the channel are the average parallel-channel Bhattacharyya noise parameter, the average channel mutual information, and parallel Gaussian channel signal-to-noise ratios (SNRs). Code parameters include the union-Bhattacharyya noise threshold and the weight spectrum distance to the random binary code ensemble. Reliable channel regions of repeat-accumulate (RA) codes for parallel binary erasure channels (BECs) and of turbo codes for parallel additive white Gaussian noise (AWGN) channels are numerically computed and compared with simulation results based on iterative decoding. In addition, an examp