Jin-Tae Park, In-Soo Koo, Ki-Seon Kim, Journal of Internet Computing and Services, Vol. 8, No. 4, pp. 1-10, Aug. 2007
Full Text:
Keywords: Wireless Sensor Networks, Decision Fusion, Non-Gaussion Noise

Abstract

Decision fusion in wireless sensor networks under non-Gaussian noise channels is studied. To consider the tail behavior noise distributions, we use a exponentially-tailed distribution as a wide class of noise distributions. Based on a canonical parallel fusion model with fading and noise channels, the likelihood ratio(LR) based fusion rule is considered as an optimal fusion rule under Neyman-Pearson criterion. With both high and low signal-to-noise ratio (SNR) approximation to the optimal rule, we obtain several suboptimal fusion rules. and we propose a simple fusion rule that provides robust detection performance with a minimum prior information, Performance evaluation for several fusion rules is peformed through simulation. Simulation results show the robustness of the Proposed simple fusion rule.

Statistics
Cite this article