Abstract
A gradient descent, iterative soft-decision algorithm for decoding Reed-Solomon codes using adaptive parity check matrices has been proposed recently. This algorithm outperforms all known Reed-Solomon soft-decoding algorithms at moderate SNR. However, many applications operate at a high SNR with frame error rate requirements in the range of 10 10 - 10 -20. At these frame error rates, simulation based performance validation is prohibitive. In this paper, we present a model to analytically compute the soft-decoding algorithm performance. Using the insight obtained from this model, we propose a low complexity, non-iterative algorithm using adaptive parity check matrices, with a similar decoding performance as the original iterative algorithm. We also propose an extension to the non-iterative algorithm which improves on the decoding performance of the iterative algorithm.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1995-1999 |
| Number of pages | 5 |
| Journal | Conference Record - Asilomar Conference on Signals, Systems and Computers |
| Volume | 2 |
| State | Published - 2004 |
| Event | Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 7 2004 → Nov 10 2004 |
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications