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Low-complexity cooperation with correlated sources: Diversity order analysis

机译:与相关源的低复杂度合作:多样性顺序分析

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Wireless sensor networks, which consist of numerous devices that take measurements of a physical phenomenon, are commonly used to observe phenomena that are correlated in space. In this paper, we devise a low-complexity coding scheme for correlated sources based on Slepian-Wolf compression, and analyze its performance in terms of diversity order. The main idea of this scheme is to use the correlated measurements as a substitute for relay links. Although we show that the asymptotic diversity order is limited by the constant correlation factor, we give experimental results that show excellent performance over practical ranges of SNR.
机译:无线传感器网络通常由用来测量物理现象的众多设备组成,用于观察与空间相关的现象。在本文中,我们设计了一种基于Slepian-Wolf压缩的相关源低复杂度编码方案,并根据分集顺序分析了其性能。该方案的主要思想是使用相关的测量值来代替中继链路。尽管我们表明渐近分集阶数受常数相关因子的限制,但我们给出的实验结果表明,在SNR的实际范围内,其性能优异。

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