A new algorithm for the LogMAP decoding of linear block codes is considered. The decoding complexity is evaluated analytically and by computer simulation. The proposed algorithm is an improvement of the recursive LogMAP algorithm proposed by the authors. The recursive LogMAP algorithm is more efficient than the BCJR algorithm for low-rate codes, but the complexity grows considerably large for high-rate codes. The aim of the proposed algorithm is to solve the complexity explosion of the recursive LogMAP algorithm for high-rate codes. The proposed algorithm is more efficient than the BCJR algorithm for well-known linear block codes.

Turbo coding is a powerful coding technique that can provide highly reliable data transmission at extremely low signal-to-noise ratios. Owing to the computational complexity of the employed decoding algorithm, the realization of turbo decoders usually takes a large amount of memory space and potentially long decoding delay. Therefore, an efficient memory management strategy becomes one of the key factors toward successfully implementing turbo decoders. This paper focuses on the development of general structures for efficient memory management of turbo decoders employing the sliding-window (Log-) MAP algorithm. Three different structures and the associated mathematic representations are derived to evaluate the required memory size, average decoding rate, and latency based on the speed and the number of the adopted processors. Comparative results show the dependency of the resulting performance based on a set of parameters; thus provide useful and general information on practical implementations of turbo decoders.

A new algorithm for the maximum a posteriori (MAP) decoding of linear block codes is presented. The proposed algorithm can be regarded as a conventional BCJR algorithm for a section trellis diagram, where branch metrics of the trellis are computed by the recursive MAP algorithm proposed by the authors. The decoding complexity of the proposed algorithm depends on the sectionalization of the trellis. A systematic way to find the optimum sectionalization which minimizes the complexity is also presented. Since the algorithm can be regarded as a generalization of both of the BCJR and the recursive MAP algorithms, the complexity of the proposed algorithm cannot be larger than those algorithms, as far as the sectionalization is chosen appropriately.

New algorithms for the MAP (also known as the APP) decoding and the MAX-LogMAP decoding of linear block codes are presented. The algorithms are devised based on the structural properties of linear block codes, and succeeds in reducing the decoding complexity without degrading the error performance. The proposed algorithms are suitable for the parallel and pipeline processing which improves the throughput of the decoder. To evaluate the decoding complexity of the proposed algorithms, simulation results for some well-known codes are presented. The results show that the algorithms are especially efficient than the conventional BCJR-based algorithms for codes whose rate are relatively low.

In this paper, we state some noteworthy facts in connection with simplification of the BCJR algorithm using the bidirectional Viterbi algorithm (BIVA). That is, we clarify the necessity of metric correction in the case that the BIVA is applied to reliability estimation, where information symbols uj obey non-uniform probability distributions.