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The advent of turbo codes in 1993 represented a significant step towards realising the ultimate capacity limit of a communication channel, breaking the link that was binding very good performance with exponential decoder complexity. Turbo codes are parallel concatenated convolutional codes, decoded with a suboptimal iterative algorithm. The complexity of the iterative algorithm increases only linearly with block length, bringing previously unprecedented performance within practical limits. This work is a further investigation of turbo codes and other concatenated schemes such as the multiple parallel concatenation and the serial concatenation. The analysis of these schemes has two important aspects, their performance under optimal decoding and the convergence of their iterative, suboptimal decoding algorithm. The connection between iterative decoding performance and the optimal decoding performance is analysed with the help of computer simulation by studying the iterative decoding error events. Methods for good performance interleaver design and code design are presented and analysed in the same way. The optimal decoding performance is further investigated by using a novel method to determine the weight spectra of turbo codes by using the turbo code tree representation, and the results are compared with the results of the iterative decoder. The method can also be used for the analysis of multiple parallel concatenated codes, but is impractical for the serial concatenated codes. Non-optimal, non-iterative decoding algorithms are presented and compared with the iterative algorithm. The convergence of the iterative algorithm is investigated by using the Cauchy criterion. Some insight into the performance of the concatenated schemes under iterative decoding is found by separating error events into convergent and non-convergent components. The sensitivity of convergence to the Eb/Ng operating point has been explored.

The performance of turbo codes can often be improved by improving the weight spectra of such codes. Methods of producing the weight spectra of turbo codes have been investigated and many improvements were made to refine the techniques. A much faster method of weight spectrum evaluation has been developed that allows calculation of weight spectra within a few minutes on a typical desktop PC. Simulation results show that new high performance turbo codes are produced by the optimisation methods presented. The two further important areas of concern are the code itself and the decoding. Improvements of the code are accomplished through optimisation of the interleaver and choice of constituent coders. Optimisation of interleaves can also be accomplished automatically using the algorithms described in this work. The addition of a CRC as an outer code proved to offer a vast improvement on the overall code performance. This was achieved without any code rate loss as the turbo code is punctured to make way for the CRC remainder. The results show a gain of 0.4dB compared to the non-CRC (1014,676) turbo code. Another improvement to the decoding performance was achieved through a combination of MAP decoding and Ordered Reliability decoding. The simulations show a performance of just 0.2dB from the Shannon limit. The same code without ordered reliability decoding has a performance curve which is 0.6dB from the Shannon limit. In situations where the MAP decoder fails to converge ordered reliability decoding succeeds in producing a codeword much closer to the received vector, often the correct codeword. The ordered reliability decoding adds to the computational complexity but lends itself to FPGA implementation.