Optimal Compression and Transmission Rate Control for Node-Lifetime Maximization

TL;DR

This paper develops optimal data compression and transmission strategies for energy-constrained sensor nodes to maximize their lifetime, considering various channel information scenarios and delay constraints.

Contribution

It introduces a joint optimization framework for compression and transmission that significantly extends sensor lifetime compared to transmission-only approaches.

Findings

Joint optimization extends sensor lifetime by 90% to 2000%.

Performance gains are greatest under strict delay constraints.

The approach adapts to different channel information scenarios.

Abstract

We consider a system that is composed of an energy constrained sensor node and a sink node, and devise optimal data compression and transmission policies with an objective to prolong the lifetime of the sensor node. While applying compression before transmission reduces the energy consumption of transmitting the sensed data, blindly applying too much compression may even exceed the cost of transmitting raw data, thereby losing its purpose. Hence, it is important to investigate the trade-off between data compression and transmission energy costs. In this paper, we study the joint optimal compression-transmission design in three scenarios which differ in terms of the available channel information at the sensor node, and cover a wide range of practical situations. We formulate and solve joint optimization problems aiming to maximize the lifetime of the sensor node whilst satisfying specific delay and bit error rate (BER) constraints. Our results show that a jointly optimized compression-transmission policy achieves significantly longer lifetime (90% to 2000%) as compared to optimizing transmission only without compression. Importantly, this performance advantage is most profound when the delay constraint is stringent, which demonstrates its suitability for low latency communication in future wireless networks.