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This paper investigates the effect of channel estimation error (CEE) on the performance of distributed estimation of an unknown parameter in wireless sensor networks (WSNs). Firstly, considering the maximum likelihood estimator (MLE) of the unknown parameter has a high complexity preventing its practical implementation, a suboptimal ML estimator is derived as a low complexity alternative. Considering...
This paper considers the optimal power scheduling for the distributed estimation of a source parameter using quantized samples of noisy sensor observations in a wireless sensor network (WSN). Repetition codes are used to transmit quantization bits of sensor observations to achieve unequal error protection, and a quasi-best linear unbiased estimate is constructed to estimate the source parameter at...
This paper presents a new progressive distributed estimation scheme (DES) along with the power scheduling among sensors under AWGN channels. The progressive DES consists of a transmission bit allocation scheme and a quasi best linear unbiased estimate (BLUE) of the unknown parameter at each sensor. This scheme is shown to outperform the traditional progressive DES. Moreover, the power scheduling among...
This letter analyzes the performance of several typical one-bit universal distributed estimation schemes (DESs) in bandwidth-constrained sensor networks. We theoretically obtain the mean and mean-square error (MSE) of the DES based on binary form (BF) of the observation along with the MSE upper bound. It is proved that in some cases, the BF-based DES has larger MSE than the DES based on the complementary...
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