Turbo codes for data compression and joint source-channel coding

We exploit the power of turbo-like codes (mainly turbo codes) in the fields of source coding and joint source channel coding, with the objective of achieving performance close to the theoretical limits. Turbo codes are well known for their near Shannon limit performance in noisy channels. However, those "random-like" codewords also allow for compression rates close to the theoretical limits when applied to source coding.; Besides the particular case of single sources, we are more interested in the general case of compression and joint source channel coding of correlated sources, which is of interest in many practical applications such as sensor networks. Different correlation models between the sources and different channel environments (independent or multiple-access AWGN/fading channels) have been considered in this dissertation. The resulting performance is always very close to the theoretical limits. Moreover, the encoding process is independent for each source and the correlation model can be estimated in the decoder site without a priori knowledge. Especially for joint source-channel coding, the simplicity at the encoder sites facilitates the implementation of the proposed scheme in practical applications, and the use of a single encoder stage in each source prevents error propagation.