Abstract
This thesis presents three novel low complexity decoding algorithms for Cyclic codes. These algorithms are the Extended Kasami Algorithm (EKA), Permutation Error Trapping (PET) and the Modified Dorsch Algorithm (MDA). The Extended Kasami Algorithm is a novel decoding algorithm combining the Error Trapping Algorithm with cover polynomial techniques. With a revised searching method to locate the best combination of cover positions, the Extended Kasami Algorithm can achieve bounded distance performance with complexity many times lower than other efficient decoding algorithms. In comparison with the Minimum Weight Decoding (MWD) Algorithm on (31,16) BCH codes, the complexity of EKA is only 5% of MWD at 0 dB Eb/No. Comparing EKA with the Kasami Algorithm on the (23,12) Golay code, EKA reduces the complexity consistently for all values of Eb/No. When dealing with Reed Solomon codes, it is found that the additional complexity incurred by finding the error values is a function that increases exponentially with the number of bits in each symbol. To eliminate the problem of finding the error values, Permutation Error Trapping uses a specific cyclic code property to re-shuffle symbol positions. This complements well the Error Trapping approach and most decodable error patterns can be trapped by using this simple approach. PET achieves performance close to that of MWD on the (15,9) RS code with much lower complexity. For more complex codes, like the four-symbol-error correcting (15,7) RS code. Modified Permutation Error Trapping combines part of the cover polynomial approach of EKA with PET resulting in retaining good performance with low complexity. For attempting to decode Reed Solomon codes using soft decision values, the application of a modified Dorsch Algorithm to Reed Solomon codes on various issues has been evaluated. Using a binary form of Reed Solomon codes has been found to be able to achieve near maximum likelihood performance with very few decodings.