Joint Source-Channel Optimization of Vector Quantization with Polar Codes

Joint application of polar channel coding combined with vector quantization lossy source coding is considered in this paper. The existing index assignment schemes in the literature cannot be used with polar codes due to their unique crossover probabilities. We elaborate on this problem and locally optimize index assignments. In addition, we propose an algorithm that jointly optimizes the number of quantization levels and the rate of the polar code in order to achieve minimum end-to-end distortion. It finds the optimal tradeoff between the distortion caused by channel errors and the quantization distortion. We also derive estimates for the crossover probabilities of the polar code which are required in the analysis. Simulation results confirm the effectiveness of the proposed algorithms and the accuracy of the crossover probabilities.