A new method of combined source-channel coding for the scalar quantization of a discrete memoryless source is presented, which takes advantage of the reliability information produced by a soft-output channel decoder. Numerical results are presented for a memoryless Gaussian source in conjunction with turbo code showing up to 1-dB improvement in the end-to-end distortion with respect to a traditional channel optimized scalar quantizer. The results include a Gaussian source designed using closed-form expression without the need for a training sequence, as well as image pixels using a training sequence. Furthermore, certain issues related to the effect of the channel mismatch and spectral efficiency of the system are studied. It is shown that the increase in distortion due to a channel mismatch can be substantially reduced by using an adaptive receiver.
['Jan Bakus', 'Amir K. Khandani']
Quantizer design for channel codes with soft-output decoding