Conditional downsampling for energy-efficient communications in wireless sensor networks

Abstract

This paper deals with the power limitations in a wireless sensor network scenario. Concretely, we propose to use a conditional downsampling encoder (CDE) at the sensing nodes as an energy-efficient solution for the communication problem. It exploits the knowledge about the signal structure, which is assumed to be time-correlated, in order to decrease the sampling rate and hence to reduce the number of transmissions within the network. We analytically assess the performance of the CDE in terms of quadratic distortion, from which we derive closed-form expressions when it is combined with one of the two decoders: the step decoder and the predictive decoder. Moreover, we propose two methodologies to design the CDE in order to guarantee a given coding rate. We also compare the CDE, both analytically and experimentally, with other classical decimator techniques, which are the deterministic downsampling encoder and the probabilistic downsampling encoder. Numerical simulation validates our analytical results. Moreover, we compare the obtained quadratic distortion and extract the conclusions of the capabilities of the studied encoding-decoding schemes.