For binary linear block codes, this letter deals with a class of decoding algorithms which utilize bounded-distance and encoding-based decodings with input sequences that are calculated from a received sequence and given test patterns. We propose a new method for selecting the test patterns by simulation. The effectiveness of the decoding algorithm whose test patterns are selected by the proposed method is also shown by simulation.

We consider an iterative decoding algorithm by using algebraic decoding for non-binary codes. In the decoding algorithm, algebraic decoding are carried out with respect to successively chosen input words, called the search centers. We present a new method for selecting sequences of search centers of algebraic decoding. Over the AWGN channel using BPSK signaling, we show simulation results on the error performances of the iterative decoding algorithms whose search centers are given by the proposed method, abbreviated IAD, for Reed-Solomon codes. From the simulation results, IAD provides considerably better error performance than GMD and CGA decoding with the same number of iterations.

We consider the binary images of (8, 5) shortened cyclic codes. The (8, 5) shortened cyclic codes have a variety of choices. We have generated about 30000 sample codes with different weight distributions. Let S/sub w/ denote the set of generated sample codes with minimum weight w. The largest minimum weight of sample codes is 8. Let A/sub w/ denote the number of codewords of weight w of a sample code. In S/sub 7/, the smallest of A/sub 7/ is 10 for 10 sample codes and the second smallest of A/sub 7/ is 11 for six sample codes. In S/sub 7/, the smallest of A/sub 8/ is 728 for a sample code and the second smallest of A/sub 8/ is 729 for a sample code. We have chosen two sample codes from each of S/sub 7/ and S/sub 8/ which have the smallest and the second smallest sums of A/sub w/ for 7/spl les/w/spl les/9 in S/sub 7/ and S/sub 8/, respectively. For the AWGN channel using BPSK signaling, we have made simulation to evaluate the decoding error probabilities by a soft-decision decoding based on ordered statistics for the chosen four sample codes at SNR 2.0 to 5.0. These error probabilities are considerably smaller than the optimum error probabilities for (64, 40) subcodes of (64, 42) Reed-Muller code.