Rate and power allocation under the pairwise distributed source coding constraint

TL;DR

This paper addresses optimal rate and power allocation in sensor networks with pairwise distributed source coding constraints, proposing graph-based solutions that outperform previous methods, especially with highly correlated sources.

Contribution

It introduces novel graph algorithms for minimum sum rate and power allocation under pairwise distributed source coding constraints in sensor networks.

Findings

Graph-based algorithms effectively find minimum sum rate and power allocations.

Proposed solutions outperform previous methods in simulations.

Significant gains observed with high source correlation.

Abstract

We consider the problem of rate and power allocation for a sensor network under the pairwise distributed source coding constraint. For noiseless source-terminal channels, we show that the minimum sum rate assignment can be found by finding a minimum weight arborescence in an appropriately defined directed graph. For orthogonal noisy source-terminal channels, the minimum sum power allocation can be found by finding a minimum weight matching forest in a mixed graph. Numerical results are presented for both cases showing that our solutions always outperform previously proposed solutions. The gains are considerable when source correlations are high.