Iterative Unequal Length Search Syndrome Decoding for Product Codes

In this paper, Iterative Unequal Length Search (ULS) Syndrome Decoding for Product Codes is proposed by introducing an idea of unequal length search space. The principle and realization of the algorithm is presented. Moreover, a mathematical performance and decoding complexity analysis is illustrated. Compared to the conventional Equal Length Search (ELS) Syndrome algorithm, experimental results indicate that the iterative ULS syndrome decoding algorithm, not only significantly reduces the decoding complexity, but also improves the error-correcting performance. Because of the balance between the odd and even circuits, the speed of parallel processing is increased and hardware resources are saved accordingly. Simulations results have shown that the proposed algorithm leads to a decrease of 25%~30% of search complexity and a gain of 0.3 dB in the BER performance for various subcodes.