Design of channel-optimized vector quantizers in the presence of channel mismatch

We study the design of channel-optimized vector quantizers in the presence of channel mismatch, We show that when the statistics of the channel bit-error rate (BER) are not known, a minimax solution is the one obtained by designing for the worst possible channel. Then, we consider the case when the probability density function of channel BER is known and propose an algorithm that provides a minimum average distortion. Also, by using an estimate of the channel BER at the decoder, we develop a decoder-adaptive scheme that further improves the performance. In all cases, me have limited ourselves to table-lookup decoders, which amount to very small computational complexities. Finally, the utilization of lookup tables at the encoder and the effects of imperfect estimation of channel BER's are considered.