Tradeoff Between Source and Channel Coding for Erasure Channels

TL;DR

This paper explores the optimal balance between source and channel coding for erasure channels, deriving bounds on coding rates and packet sizes to minimize end-to-end distortion using theoretical error exponents and quantization theory.

Contribution

It introduces new bounds on channel coding rates and packet sizes for erasure channels, combining multiple theoretical approaches to optimize end-to-end distortion.

Findings

Derived upper and lower bounds on channel coding rate

Established bounds on packet size for given distortion limits

Applied combined theoretical methods for bound calculation

Abstract

In this paper, we investigate the optimal tradeoff between source and channel coding for channels with bit or packet erasure. Upper and Lower bounds on the optimal channel coding rate are computed to achieve minimal end-to-end distortion. The bounds are calculated based on a combination of sphere packing, straight line and expurgated error exponents and also high rate vector quantization theory. By modeling a packet erasure channel in terms of an equivalent bit erasure channel, we obtain bounds on the packet size for a specified limit on the distortion.