Adaptive remote signal coding and recovery in wireless sensor networks

Distributed source coding has been viewed as an important and challenging technique for the problem of signal recovery in wireless sensor networks, due to limited network bandwidth, processing capability, and power. In this paper, the problem of signal recovery in wireless sensor networks is studied by leverage of side information and distributed source coding. The available bandwidth and packet loss rate are assumed to be changing in the delivery path from remote sensors to sink. We first analyze the impact of quantization, random binning, and transmission on the quality of estimated signal. Then we propose an adaptive control scheme to trade off bandwidth on quantization, random binning, and transmission under specific network scenarios. Numerical results validate the effectiveness of the proposed adaptive control scheme on minimizing system distortion.