Power Reduction in Heterogeneous Wireless Sensor Networks via Source-Aware Allocation

Abstract

Heterogeneous wireless sensor networks (HWSNs) in space and extreme environments must reliably transmit diverse analog physical signals over resource-constrained fading channels, subject to bandwidth limitations, power budgets, and reconstruction quality requirements. This paper addresses two fundamental questions: (i) what is the minimum signal-to-noise ratio (SNR) a sensing link must sustain to reconstruct an analog signal at a prescribed distortion, regardless of the decoder used, and (ii) how can knowledge of the signal's intrinsic structure be exploited to jointly allocate power and bandwidth across an HWSN? Both questions are answered through the Renyi information dimension (RID), which quantifies the intrinsic complexity of an analog source distribution. By combining the RID with rate-distortion theory and Shannon channel capacity, a closed-form SNR lower bound is derived, parameterized solely by the source RID. Building on these foundations, a cross-layer resource allocation framework is introduced that exploits the per-node RID to jointly assign transmit power and bandwidth, achieving strict power saving relative to a Gaussian-assumption baseline while guaranteeing prescribed reconstruction quality and outage constraints at every node.