Soft Reed-Solomon decoding for concatenated codes

This paper analyzes two soft-input Reed-Solomon (RS) decoding methods, generalized minimum distance (GMD) decoding and the chase-GMD algorithm (CGA), applying them to concatenated codes. Using as an example an encoding scheme combining convolutional and RS encoders, the performance of different decoding approaches is evaluated in AWGN and Rayleigh channels by means of numerical simulations. It is shown that in AWGN channel, soft-input decoding improves slightly the block error rate (BLER) performance when compared to hard decoding; no significant improvement is obtained for Rayleigh channels. We observe that CGA decoding looses its advantage over GMD when applied to concatenated codes. We conclude the work analyzing the reliability of soft-input decoding and measures for its improvement.