On diversity schemes in decentralized estimation

Alex S. C. Leong, S. Dey
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Abstract

This paper is concerned with the decentralized estimation of a Gaussian source using multiple sensors. We consider a diversity scheme where only the sensor with the best channel sends their measurements to a fusion center, using the analog amplify and forwarding technique. A distributed version of the diversity scheme where sensors decide what to transmit based only on their local information is also considered. We derive asymptotic expressions for the expected distortion of these schemes as the number of sensors becomes large. We also study the optimal power allocation problem for minimizing the expected distortion subject to average power constraints.
分散估计中的分集方案
本文研究了利用多传感器对高斯源进行分散估计的问题。我们考虑了一种分集方案,其中只有具有最佳信道的传感器使用模拟放大和转发技术将其测量值发送到融合中心。还考虑了分集方案的分布式版本,其中传感器仅根据其本地信息来决定传输什么。随着传感器数量的增加,我们得到了这些方案的期望畸变的渐近表达式。我们还研究了在平均功率约束下最小化期望失真的最优功率分配问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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