CORTEXA
← Browse
arxiveess.SP2026-07-13

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

Mauro Marchese, Pietro Savazzi

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.

View free PDFSource page

Related papers

arxiveess.AScs.ITeess.SP2026-07-06

Distributed Multichannel Wiener Filtering for Topology-Unconstrained Wireless Acoustic Sensor Networks

Paul Didier, Pourya Behmandpoor, Henri Gode, Toon van Waterschoot, Simon Doclo, Jörg Bitzer, et al.

This paper introduces the topology-independent distributed multichannel Wiener filter (TI-dMWF), a novel algorithm for distributed node-specific signal estimation in wireless acoustic sensor networks (WASNs) with unconstrained topologies. The TI-dMWF enables each node in the netw…

View free PDFSource page
arxiveess.SP2026-07-02

Rethinking Fractional Programming for Joint Uplink Scheduling and Power Control in Multicell Wireless Networks

Zihan Jiao, Xinping Yi, Shi Jin, Giuseppe Caire

This paper investigates the joint uplink scheduling and power control problem in a coordinated multicell wireless network, where at most one single-antenna user is allowed to access the single-antenna base station in each cell simultaneously. The resulting weighted sum-rate (WSR)…

View free PDFSource page
arxivcs.ITeess.SPmath.DSmath.PR2026-06-28

Dynamical System Characterization of Heterogeneous Walker Satellite Networks: An Orbit-Aware Stochastic Geometry Perspective

Chang-Sik Choi, Francois Baccelli

Heterogeneous and in particular multi-altitude low Earth orbit (LEO) satellite constellations exhibit complex spatial and temporal structures, which require new modeling tools for their performance analysis. In this paper, we develop an orbit-aware stochastic geometry framework m…

View free PDFSource page
arxivcs.LGcs.AIcs.ITeess.SP2026-07-20

Multi-layer MIMO Relay as Deep Physical Neural Networks: Power Amplifiers as Activation Functions

Meng Hua, Itsik Bergel, Deniz Gündüz

Wireless physical neural networks (WPNNs) embed neural computation directly into analog hardware, offering lower energy consumption and latency than conventional digital implementations. In this paper, we propose a deep WPNN in which nonlinear activations are realized by a multi-…

View free PDFSource page
arxiveess.SP2026-07-31

Safety Analysis of Metasurface-Based Near-field Wireless Power Transfer System for Deep Implant

Maoyuan Li, Ali Khaleghi, Ilangko Balasingham

Wireless power transfer is a method for energizing future implantable medical electronics. In this study, a metasurface-based near-field magnetic wireless power transfer system for deep implants is presented, and electromagnetic safety parameters, including field distributions, s…

View free PDFSource page