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Distortion sum-rate performance of successive coding strategy in quadratic gaussian CEO problem

机译:二次高斯CEO问题中连续编码策略的失真总和性能

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摘要

We consider a distributed sensor network, modeled by the CEO problem, in which each sensor communicates its observation to the fusion center (FC) using limited transmission rate. Based on the successive coding strategy, we obtain the optimal rate allocation strategy for the Gaussian CEO problem which minimizes the average distortion in the source estimate produced by the FC. This strategy can be simplified in a general parallel sensor network with L sensors by assigning equal rates to sensors if the sum-rate R macr is very large given a fixed L or if L is very large given a fixed R macr.
机译:我们考虑一个由CEO问题建模的分布式传感器网络,其中每个传感器使用有限的传输速率将其观测结果传达给融合中心(FC)。基于连续编码策略,我们获得了针对高斯CEO问题的最佳速率分配策略,该策略将FC产生的源估计中的平均失真最小化。如果总速率R macr在给定L的情况下非常大,或者如果L在给定R macr的情况下非常大,则在具有L个传感器的通用并行传感器网络中,可以通过为传感器分配相等的速率来简化此策略。

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