Distributed estimation with convolutional coding in wireless sensor networks

The problem of distributed estimation of an unknown noise-corrupted parameter in wireless sensor networks (WSNs) is considered in this paper. Because of the impact of noise channels, convolutional coding is used to protect the transmission of sensor observations here. To minimize the total power consumption, a novel kinds of power scheduling is derived. The formulas of the proposed power scheduling suggest local sensors with poor observation qualities should decrease their quantization levels and the levels should be also related to coding methods, channel qualities, given mean squared error (MSE) and local signal-to-noise ratio (SNR). Finally, simulation results show that not only is the scheme energy-efficient but also it achieves comparable performance of a given MSE.