The performance of a relatively simple two-dimensional (2-D) product code is considered. The row code is a short constraint length convolutional code, and the column code is a high-rate block code. Both the rows and columns are decoded with soft-decision maximum likelihood decoding. The soft output Viterbi algorithm (SOVA) is used to decode the rows. In one case, the same decoder may be used for the rows and the columns. It is shown that, depending on the rate of the row code, reliable signaling is achieved within about 1.0 to 1.5 dB of the R/sub 0/ limit. Results are given for a particular impulsive noise channel; it is seen that performance is robust over a wide range of channel conditions.

Use of the Viterbi decoder to decode the (63, 57) Hamming code is considered, Implementation and performance of systematic and nonsystematic codes are addressed. It is shown that a Viterbi decoder for the constraint length seven, rate- 1/2 convolutional code can be used to decode both systematic and nonsystematic (63, 57) Hamming codes, but an additional step is needed to complete the decoding of the systematic code. Bounds and simulation results for postdecoding bit-error probability are given and it is shown that the systematic code performs 0.4 dB better than the nonsystematic code. A heuristic explanation is provided.

We present a technique for calculating the bit error rate performance of nonlinear demodulators operating in impulsive noise in the limit of large time-bandwidth products. The asymptotic limit is given, together with first- and second-order corrections. We calculate bit error rates with two nonlinearities, a bandpass limiter and a low-pass limiter; the two are found to give very similar results. The computational technique is applicable to all noise distributions. We present results for two distributions, an analytic continuation of the Hall model and a truncated Hall mode. The models yield significantly different results.