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In this paper, we study one-bit quantizer design for distributed estimation under the minimax criterion for wireless sensor network (WSN) applications. Identical local quantizers are generally difficult to design because of the dependence on the unknown parameter under estimation. Nonidentical local quantizers are more robust in that sense. However, its design generally involves multi-dimensional...
The problem of distributed estimation of an unknown parameter in noise is revisited. To meet the stringent bandwidth and energy constraints in practical wireless sensor network (WSN) applications, a one-bit quantization scheme is adopted to compress local sensor observations. Imperfect communication between local sensors and the fusion center is considered and modeled as a flat fading channel. Due...
In this paper, the problem of distributed estimation using one-bit quantization in the presence of non-ideal transmission links is revisited. Previous results have shown that the estimation performance highly depends on the selection of local quantization thresholds. Both the identical threshold scheme and the non-identical threshold scheme are investigated under the minimax criterion. Specifically,...
The problem of distributed estimation of an unknown parameter in noise is considered. Sensor observations are compressed using a one-bit quantizer and then transmitted to a fusion center over fading channels. We propose a mean estimator which requires only the knowledge of the mean of the channel gain and a sign estimator where the signs of the received signals are used for parameter estimation. Our...
The problem of distributed estimation of an unknown parameter corrupted by noise is studied in this paper. In consideration of the stringent bandwidth constraint in practical wireless sensor network (WSN) applications, a one-bit quantization scheme is adopted to compress local sensor observations. Imperfect data transmission between local sensors and a fusion center is considered and modeled as a...
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