Robustness to channel variation in source coding for transmission across noisy channels

We consider the problem of lossy source coding for transmission across an unknown or time-varying noisy channel. The objective is to design an optimal compression system for applications where the unknown channel characteristics are independently estimated at the channel encoder and decoder. Channel estimation reliability is allowed to vary from perfect channel identification to no channel identification. In each case, the goal in system design and operation is to achieve the best possible expected performance with respect to the unknown channel state and the accuracy of the channel estimators. We describe an optimal design technique and an algorithm for achieving optimal expected performance for the entire array of channel estimation accuracies. The resulting system achieves up to 9 dB improvement over the performance on a system designed assuming zero probability of error when used to encode a collection of medical brain scans for transmission across a finite state channel containing two equally probable binary symmetric channels with crossover probabilities .05 and .001.