Energy efficiency analysis of an RLS-based adaptive signal processing algorithm for energy aware sensor networks

A joint source coding and RLS-based adaptive signal processing approach that exploits the inherent correlations among the sensor data, in order to improve energy efficiency of low-power wireless sensor networks is proposed. The energy efficiency is achieved by reducing the transmission requirements from sensors. A semi-analytical technique is presented in order to determine the energy-efficiency of the proposed scheme taking into account both communications and circuit power consumptions. The numerical results obtained with real sensor data show that the proposed scheme offers significant energy savings compared to previously proposed schemes.

I. Introduction

Large-scale wireless sensor networks can be used in many ubiquitous applications such as environmental monitoring and battle-field surveillance. Nodes of these networks are generally battery operated resulting in energy-constrained sensor networks. Thus energy-aware sensor processing plays an important role in improving the life-time of the sensor network and preventing the loss of critical information due to node failures. Many approaches that facilitate energy consumption reduction in sensor networks have previously been proposed. Some of these can be found in [1]–[3] and [4].