ESPRIT-like error localization algorithm for a class of real number codes
Joint source and channel coding of multimedia data for transmission over wireless networks is a challenging task. Recently, a class of BCH-like real number codes has been considered for providing robustness to data loss or data error over such networks. Unlike finite-field codes, the real codevectors undergo a quantization process before being transmitted, and therefore, the error localization efficiency becomes algorithm-dependent. The paper presents an ESPRIT-like subspace algorithm for localizing errors in such codes and compares its performance with other known localization algorithms. In particular, we consider lowpass DFT, DCT and DST codes, and compare the localization efficiency of the ESPRIT-like algorithm with the standard BCH decoding approach and the MUSIC-like subspace approach. Simulation results with a Gauss-Markov source are presented.