Index Assignment Optimization for Joint Source-Channel MAP Decoding
Channel-optimized quantizer index assignment and maximum a posteriori (MAP) decoding have been extensively studied for error-resilient communications. An interesting and largely untreated problem is how to optimize the index assignment with respect to joint source-channel MAP decoding. In this paper we formulate the above problem as one of quadratic programming, and discuss its solutions from very general to some special cases. Experimental results are presented to demonstrate the performance improvement of the index assignments optimized for MAP decoding over those designed for hard-decision decoding.