Vector Quantization (VQ) is a source coding technique that is emerging as a fundamental component in many speech and video coding systems, particularly for low rate efficient transmission over limited capacity communication channels. The principal investigator is investigating and developing combined VQ and channel coding algorithms that substantially advance the current performance achievable with respect to the overall reproduction quality of the signal in a narrowband channel or packet network environment. In many applications limited bandwidth constraints make impractical the use of traditional channel coding techniques. The algorithms being studied will combine basic VQ compression techniques for voice and video applications with new channel coding schemes that use little or no redundancy information. The project will examine in depth and develop new source/channel techniques for VQ, exploiting combined quantization and modulation, packet error recovery, index permutations, and selective bit protection. In addition, a theoretical analysis of the performance of VQ in the presence of channel noise for asymptotically high resolution quantizers is being studied, which can lead to better understanding for quantizer design procedures.
