Data extraction from wireless sensor networks using distributed fountain codes

A Wireless Sensor Network (WSN) observes a natural field and aims to recreate it with sufficient fidelity at a, perhaps distant, Fusion Center (FC) using a wireless communication channel of arbitrary capacity. We propose a universal and power efficient method for such data extraction, based on Digital Fountain Codes (DFCs) and joint-source channel decoding. Our method implements a distributed `rate-lessiquest DFC which automatically tunes the number of transmissions to the channel capacity. Furthermore, instead of directly compressing the WSN data, we achieve rate reduction by treating the spatiotemporal dependencies in the field as an outer code, and jointly decoding this concatenation at the FC using a multi-stage iterative decoder. We demonstrate that a power efficiency close to the capacity-rate-distortion limit is achieved at moderate distortion levels, irrespective of the channel capacity or field dependencies. As compared to the traditional approach of source-channel separation, the proposed data extraction scheme is particularly attractive for WSN applications due its computationally simple encoding procedure, low latency and the ability to seamlessly trade-off fidelity of reconstruction for power consumption.