Hung-Peng Lee, Hsin-Chiu Chang
Automatic Control and Information Sciences. 2014, 2(1), 7-12DOI:
Abstract: In this paper, a more efficient syndrome-weight decoding algorithm (SWDA), called the enhanced syndrome-weight decoding algorithm (ESWDA), is presented to decode up to three possible errors for the binary systematic (23, 12, 7) and (31, 16, 7) quadratic residue (QR) codes. In decoding of the QR codes, the evaluation of the error-locator polynomial in the finite field is complicated and time-consuming. To solve such a problem, the proposed ESWDA avoids evaluating the complicated error-locator polynomial, and has no need of a look-up table to store the syndromes and their corresponding error patterns in the memory. In comparison with the SWDA developed by Lin-Chang-Lee-Truong (2010), the simulation results show that the ESWDA can serve as an efficient and high-speed decoder.