A new soft decision maximum-likelihood decoding algorithm, which generates the minimum set of candidate codewords by efficiently applying the algebraic decoder is proposed. As a result, the decoding complexity is reduced without degradation of performance. The new algorithm is tested and verified by simulation results.

With the tremendous growth in the field of communication, wireless system requires significantly higher spectral efficiency. The solution of this problem is MIMO Spatial Multiplexing (SM). In this paper we compare performance of different methods for decoding multiple input-multiple output (MIMO) transmission System incorporating VBLAST-SM, which includes sphere decoding (SD), zero forcing (ZF)...

—For the additive white Gaussian noise channel with average codeword power constraint, sparse superposition codes are developed. These codes are based on the statistical high-dimensional regression framework. The paper [IEEE Trans. Inform. Theory 55 (2012), 2541 – 2557] investigated decoding using the optimal maximum-likelihood decoding scheme. Here a fast decoding algorithm, called adaptive su...

Abstract: Two different ways of obtaining generalized low-density parity-check codes are considered. Lower bounds on the minimum distance, stopping distance, and pseudodistance are derived for these codes using graph based analysis. These bounds are generalizations of Tanner’s bit-oriented and parity-oriented bound for simple LDPC codes. The new bounds are useful in predicting the performance o...

Decoding with feedback or iterative decoding is an eecient, low-complexity means for \informa-tion handover" in any parallel or serial concate-nated coding scheme and in related applications. Invented twenty years ago, it has recently been payed considerable attention in the context of \Turbo Codes". Iterative decoding has been jus-tiied intuitively, but many question remain and perhaps will re...

We present Kovalenko’s full-rank limit as a tight lower bound for decoding error probability of LDPC codes and LT codes over BEC. From the limit, we derive a full-rank overhead as a lower bound for stable overheads for successful maximum-likelihood decoding of the codes.

In this paper we establish some criteria to decide when a discrete memoryless channel admits a metric in such a way that the maximum likelihood decoding coincides with the nearest neighbour decoding. In particular we prove a conjecture presented by M. Firer and J. L. Walker establishing that every binary asymmetric channel admits a matched metric.

Practical Viterbi decoders often fall significantly short of full maximum likelihood decoding (MLD) pe;formance because of survivor truncation efiects. In this paper, we study the tradeoff between truncation length and performance loss for the two most common variations of Viterbi’s algorithm: best state decoding (BSD) and fized state decoding (FSD). We find that FSD survivors should be about t...

− In this paper, we investigate an improved upper bound on the bit error probability of turbo codes for the maximum likelihood (ML) decoding with imperfect channel state information (CSI) in a fully interleaved Rayleigh fading channel. The upper bound is based on recently introduced Viterbi & Viterbi bound and is also compared with iterative decoding using the Log-MAP algorithm. It is shown tha...