Adaptive Joint Lossy Source-Channel Coding for Multihop IoT Networks

Abstract

We consider monitoring applications in multihop wireless sensor networks (WSNs), where nodes rely on limited batteries so that energy efficiency and reliability are of paramount importance. Typically, lossy compression is aimed at saving transmission energy, yet affects the quality of transmitted data over lossy channels. Accordingly, using error correction coding (ECC) along with compression is required to guarantee both energy efficiency and high-fidelity reconstruction. In this paper, we analyze the energy efficiency of the joint use of lossy compression along with ECC, with the twofold objective of extending the network lifetime and assuring reliability. Specifically, we consider an adaptive joint lossy source-channel coding (JLSCC) system, where the energy efficiency and reliability performances depend on both the compression and the coding rates. Therein, we first carry out a performance analysis of JLSCC, considering realistic models of communication and computational energies, when the communication is performed over a Rayleigh fading channel. Then, we evaluate the performance of the JLSCC system compared to lossy compression and ECC systems in both end-to-end and multihop communications. Our results reveal that an adaptive JLSCC results in substantial energy saving while guaranteeing the required reliability performance, compared to both lossy compression and channel coding systems, that cannot be efficient for both energy and reliability. Instead, the JLSCC system is proved to be energy efficient for small distance end-to-end communication and large-scale multihop network, while leading to satisfactory reliability performance.