Compressed Sensing Based Data Processing and MAC Protocol Design for Smartgrids

TL;DR

This paper presents a joint data compression and MAC protocol design for smartgrids using compressed sensing, aiming to reduce reporting delay and improve data recovery reliability in renewable energy systems.

Contribution

It introduces a novel joint design of 2D compressed sensing and an adapted MAC protocol for efficient data reporting in smartgrids with renewable sources.

Findings

Reduced reporting delay through optimized protocol parameters

Effective data recovery demonstrated via numerical results

Enhanced data compression leveraging data correlation in smartgrids

Abstract

In this paper, we consider the joint design of data compression and 802.15.4-based medium access control (MAC) protocol for smartgrids with renewable energy. We study the setting where a number of nodes, each of which comprises electricity load and/or renewable sources, report periodically their injected powers to a data concentrator. Our design exploits the correlation of the reported data in both time and space to perform efficient data compression using the compressed sensing (CS) technique and efficiently engineer the MAC protocol so that the reported data can be recovered reliably within minimum reporting time. Specifically, we perform the following design tasks: i) we employ the two-dimensional (2D) CS technique to compress the reported data in the distributed manner, ii) we propose to adapt the 802.15.4 MAC protocol frame structure to enable efficient data transmission and reliable data reconstruction, and iii) we develop an analytical model based on which we can obtain the optimal parameter configuration to minimize the reporting delay. Finally, numerical results are presented to demonstrate the effectiveness of our design.