Multiple Description Coding Over Correlated Channels

1. Multiple Description Coding Over Correlated Channels Investigators: Songqing Zhao; Daniela Tuninetti; Rashid Ansari; Dan Schonfeld (ECE, UIC) Primary Grant Support: University Fellowship • Multi-path routing in today’s network allows to deliver information to a receiver though different channels. • The channels are in general correlated (I.e., wireless networks), that is, reception failures on different channels are not independent. • We focus on send a single source though multiple channels by using a Multiple Description Code (MDC). • We aim to (a) find the rate allocation that minimize the average reconstruction error at the receiver, and (b) understand the effect of channel correlation on the distortion performance. Channel 1 MDC Encoder MDC Decoder Channel 2 … Channel N • For two erasure channels, we determine when MDC is better than Single Description Coding (SDC) by using Lagrange duality theory. • For block-fading Gaussian channels, we determine the optimal average distortion in the high-SNR (signal to noise ratio) regime by using the diversity-multiplexing tradeoff framework. • For block-fading Gaussian channels, we also determine the SNR-offset, that is to say, the maximum gap between the distortion in the high-SNR approximation and the actual distortion. • For erasure channels, analytical bounds and numerical results are obtained to determine when MDC or SDC is optimal. Suboptimal but simple rate allocation policies are proposed. • For fading channels, fading correlation does not affect the distortion exponent, but causes a distortion offset. • We show that determining the distortion exponent of MDC scheme for fading channels reduces to solving a linear programming problem. • Future work will extend the current results to other channel models, such as cross-interference channels and channels with power control.