Quantization and reconstruction of sources with memory

A fundamental problem in telecommunications is the reliable transmission of a source over a noisy channel. As an important result of the Shannon's celebrated paper [1], the problem can be theoretically separated, without loss of optimality, into two parts: source coding and channel coding. However, in practise, due to the strict design constraints, such as the limitations on complexity of the systems involved, the joint design of source and channel coders has found increasing interest.; This thesis deals with the design of efficient reliable communication systems with a particular emphasis on practical issues such as complexity and delay.; A low bit-rate low complexity Block-based Trellis Quantization (BTQ) scheme is proposed for the quantization of speech spectrum in speech coding applications. The proposed scheme is based on the modeling of the LSF intraframe dependencies with a trellis structure. The BTQ search and design algorithms are discussed and an efficient algorithm for the index generation is proposed. Extensive comparisons with several other techniques from the literature are provided.; Efficient source decoding schemes are presented, which take advantage of the residual redundancy in the source coder output stream as a bandwidth efficient way to combat the noisy channel degradations. This falls into the category of joint source channel (de)coding. In this part, a family of solutions is proposed for the asymptotically optimum Minimum Mean Squared Error (MMSE) reconstruction of a source over memoryless noisy channels when the residual redundancy is exploited by use of a γ-order Markov model (γ ≥ 1) and a delay of δ is allowed in the decoding process. Considering the same problem setup, several other simplified MMSE and maximum a posteriori symbol and sequence decoders are also presented.; The problem of reconstruction of the predictively quantized signals over a noisy channel is also considered. As well, methods for the reconstruction of speech encoded with the Enhanced Full Rate Codec (EFRC, IS-641) and transmitted over a noisy channel are presented. A methodology to efficiently approximate and store the a priori probabilities characterizing the residual redundancies is introduced. Numerical results are presented which demonstrate the efficiency of the proposed algorithms.