In this paper, through extrinsic information transfer (EXIT) band chart analysis, an adaptive iterative decoding approach (AIDA) is proposed to reduce the iterative decoding complexity and delay for finite-length differentially encoded Low-density parity-check (DE-LDPC) coded systems with multiple-symbol differential detection (MSDD). The proposed AIDA can adaptively adjust the observation window size (OWS) of the MSDD soft-input soft-output demodulator (SISOD) and the outer iteration number of the iterative decoder (consisting of the MSDD SISOD and the LDPC decoder) instead of setting fixed values for the two parameters of the considered systems. The performance of AIDA depends on its stopping criterion (SC) which is used to terminate the iterative decoding before reaching the maximum outer iteration number. Many SCs have been proposed; however, these approaches focus on turbo coded systems, and it has been proven that they do not well suit for LDPC coded systems. To solve this problem, a new SC called differential mutual information (DMI) criterion, which can track the convergence status of the iterative decoding, is proposed; it is based on tracking the difference of the output mutual information of the LDPC decoder between two consecutive outer iterations of the considered systems. AIDA using the DMI criterion can adaptively adjust the out iteration number and OWS according to the convergence situation of the iterative decoding. Simulation results show that compared with using the existing SCs, AIDA using the DMI criterion can further reduce the decoding complexity and delay, and its performance is not affected by a change in the LDPC code and transmission channel parameters.

A generalized algorithm for designing an optimum VQ source codec in systems with channel coding is presented. Based on an AWGN channel model, the algorithm derives the distribution of the channel decoder soft-output and substitutes it in the expression for the system end-to-end distortion. The VQ encoder/decoder pair is then optimized by minimizing this end-to-end distortion. For a Gauss-Markov source, the proposed algorithm outperforms the conventional SOVQ source coding scheme by 5.0 dB in the decoded source SNR. Application of this algorithm for designing optimum low-bit-rate speech codec is given. A 4.0 kbps VQ based CELP codec is designed for performance evaluations, where all the CELP parameter encoder/decoder pairs are optimized by minimizing their end-to-end distortions, respectively. As a result, the speech distortion over the noisy channel is minimized. Subjective tests show that the proposed algorithm improves the decoded speech quality by 2.5 MOS relative to a regular SOVQ CELP speech coding system. The performances of the algorithm under channel mismatch conditions are also shown and discussed.