Correlated data gathering in wireless sensor networks based on distributed source coding

We propose in this paper a novel scheme for correlated data gathering in energy- and bandwidth-limited wireless sensor networks based on Distributed Source Coding (DSC). We develop a special Viterbi Algorithm, denoted as VA-DSC, for decoding of the sensor data encoded by DSC. DSC principles have recently been applied to sensor data gathering by constructing practical DSC schemes using channel coding approach. However, existing schemes have not yet taken into account the inherent difference between source coding and channel coding. In this proposed algorithm, we take advantage of the known parity bits at the decoder when the data is encoded by DSC. When the proposed algorithm is applied to Recursive Systematic Convolutional (RSC) and Turbo codes, we demonstrate that VA-DSC is able to reduce both decoding error probability and computational complexity. When the proposed algorithm is applied to correlated data gathering in wireless sensor networks, we demonstrate that VA-DSC is also capable of receiving all data correctly, while, at the same time, reducing the energy consumption in the networks. Our simulation results show that the proposed scheme results in superior performance in terms of data reception accuracy and energy consumption efficiency.