Compressed Sensor Caching and Collaborative Sparse Data Recovery with Anchor Alignment

TL;DR

This paper introduces a novel distributed sparse data recovery algorithm for wireless sensor networks that leverages anchor alignment and deep unfolding to improve reconstruction quality and reduce communication overhead.

Contribution

It proposes the CoSR-AA algorithm with anchor alignment for collaborative sparse recovery and a deep unfolded version using graph neural networks for efficiency.

Findings

Enhanced data reconstruction accuracy demonstrated in simulations.

Reduced communication overhead through anchor alignment strategy.

Deep CoSR-AA significantly decreases iteration count needed for recovery.

Abstract

This work examines the compressed sensor caching problem in wireless sensor networks and devises efficient distributed sparse data recovery algorithms to enable collaboration among multiple caches. In this problem, each cache is only allowed to access measurements from a small subset of sensors within its vicinity to reduce both cache size and data acquisition overhead. To enable reliable data recovery with limited access to measurements, we propose a distributed sparse data recovery method, called the collaborative sparse recovery by anchor alignment (CoSR-AA) algorithm, where collaboration among caches is enabled by aligning their locally recovered data at a few anchor nodes. The proposed algorithm is based on the consensus alternating direction method of multipliers (ADMM) algorithm but with message exchange that is reduced by considering the proposed anchor alignment strategy. Then, by the deep unfolding of the ADMM iterations, we further propose the Deep CoSR-AA algorithm that can be used to significantly reduce the number of iterations. We obtain a graph neural network architecture where message exchange is done more efficiently by an embedded autoencoder. Simulations are provided to demonstrate the effectiveness of the proposed collaborative recovery algorithms in terms of the improved reconstruction quality and the reduced communication overhead due to anchor alignment.