Recursive syndrome decoding of DFT codes for bursty erasures

Recently DFT codes have been considered for use as joint source-channel codes in order to provide robustness against packet loss in IP networks. In this paper, we propose a recursive syndrome decoding algorithm of DFT codes for bursty erasure patterns. The algorithm is based on the statistical properties of the quantization error and the codevector. The statistical analysis of the codevector is independent of the proposed algorithm. We also analyze the error performance of the proposed decoding scheme, and show that it can perform better than the conventional syndrome decoding of DFT codes if the message signal model and quantization error model assumptions are valid. Simulation results with a Gauss-Markov source are presented.