Based on the Berlekamp-Massy （BM） algorithm for Reed-Solomon（RS） decoding, an improved version is proposed, which focuses on how to find the error locator polynomial using least iterative operations. The condition...Based on the Berlekamp-Massy （BM） algorithm for Reed-Solomon（RS） decoding, an improved version is proposed, which focuses on how to find the error locator polynomial using least iterative operations. The conditions to end the iterative operations is derived. As a special case, criterion of only one error symbol in one received codeword is derived as well. Steps are listed concerning the implementation of the improved iterative decoding algorithm, which is carried out as software on the platform of TI＇s C6416 DSP. Decoding performance and decoding-delay of both improved and original algorithms under different （n,k） conditions are simulated. The results of simulations demonstrate that the improved algorithm has less computational complexity when the number of errors in a received codeword is relatively small. Therefore, in channels with low noise power spectrum density, the improved algorithm results in less decoding-delay than BM algorithm.展开更多
The article analyzes the classical BM algorithm and an improved algorithm, and then it puts forward a new improved algorithm which called I_BM algorithm according to the characteristics of the string matching. The I_B...The article analyzes the classical BM algorithm and an improved algorithm, and then it puts forward a new improved algorithm which called I_BM algorithm according to the characteristics of the string matching. The I_BM algorithm determines the right distance according to the first character of the pattern string and the distance between the matching windows, so it fasts matching. The matching way of I_BM algorithm is from right to left. In order to verify the IBM algorithm＇ s performance, it does experiments on I_BM algorithm from two aspects of the matching times and the numbers of matching characters under the condition of the same text strings and pattem string. The experimental results show that I_BM algorithm is more quickly and more efficient because it reduces greatly the number of matching and character comparison for maximizing to skip the bad characters.展开更多
基金Sponsored by the National High Technology Research and Development Program of China ("863"Program) (2007AA01Z293)
文摘Based on the Berlekamp-Massy （BM） algorithm for Reed-Solomon（RS） decoding, an improved version is proposed, which focuses on how to find the error locator polynomial using least iterative operations. The conditions to end the iterative operations is derived. As a special case, criterion of only one error symbol in one received codeword is derived as well. Steps are listed concerning the implementation of the improved iterative decoding algorithm, which is carried out as software on the platform of TI＇s C6416 DSP. Decoding performance and decoding-delay of both improved and original algorithms under different （n,k） conditions are simulated. The results of simulations demonstrate that the improved algorithm has less computational complexity when the number of errors in a received codeword is relatively small. Therefore, in channels with low noise power spectrum density, the improved algorithm results in less decoding-delay than BM algorithm.
文摘The article analyzes the classical BM algorithm and an improved algorithm, and then it puts forward a new improved algorithm which called I_BM algorithm according to the characteristics of the string matching. The I_BM algorithm determines the right distance according to the first character of the pattern string and the distance between the matching windows, so it fasts matching. The matching way of I_BM algorithm is from right to left. In order to verify the IBM algorithm＇ s performance, it does experiments on I_BM algorithm from two aspects of the matching times and the numbers of matching characters under the condition of the same text strings and pattem string. The experimental results show that I_BM algorithm is more quickly and more efficient because it reduces greatly the number of matching and character comparison for maximizing to skip the bad characters.
