不可靠报告通道的分布式检测:量化还是不量化?

Lei Cao, R. Viswanathan
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引用次数: 1

摘要

众所周知,将传感器观测到的原始数据完整且无信道失真地报告到融合中心总是比报告量化数据表现得更好。然而,当信道噪声一直存在时,我们表明发送未量化的原始数据还是量化的数据是一个非常有趣的问题,需要更多的研究工作。我们在使用相同的传输功率和带宽的约束下比较了这两种方案,其中假设每个信道使用模拟调制。从贝叶斯误差的角度给出了单传感器和双传感器的检测性能。比较了渐近多传感器与切尔诺夫信息的性能。本文的研究为优化分布式检测系统的设计提供了一个新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Distributed Detection with Unreliable Reporting Channels: Quantize or Not Quantize?
It is known that reporting the raw data observed at sensors to the fusion center completely and without any channel distortion always performs better than reporting the quantized data. However, when channel noise exists as it is always in practice, we show whether it is optimal to send the unquantized raw data or quantized data is a very interesting question that requires more research efforts. We compare these two schemes under the constraints of using the same transmission power and the bandwidth where analog modulation is assumed per channel use. The detection performance with one sensor and two sensors is presented in terms of the Bayes error. The performance of using asymptotically many sensors is compared with the Chernoff information. What presented in the paper could open up a new perspective in the design of the optimal distributed detection systems.
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