This paper addresses the problem of distributed detection of stochastic sparse signals in a wireless sensor network. Observations/local likelihood ratios in each sensor node are quantized into 1-bit and sent to a fusion center (FC) through non-ideal channels. At the FC, More
This paper addresses the problem of distributed detection of stochastic sparse signals in a wireless sensor network. Observations/local likelihood ratios in each sensor node are quantized into 1-bit and sent to a fusion center (FC) through non-ideal channels. At the FC, we propose two sub-optimal detectors after that the data are fused based on the locally most powerful test (LMPT). We obtain the quantization threshold for each sensor node via an asymptotic analysis of the performance of the detector. It is realized that the quantization threshold depends on the bit error probability of the channels between the sensor nodes and the FC. Simulation results are carried out to confirm our theoretical analysis and to depict the performance of the proposed detectors.
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