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Joint Source-Channel-Network Decoding and Blind Estimation of Correlated Sensors Using Concatenated Zigzag Codes

机译:使用级联之字形码的联合源-信道-网络解码和相关传感器的盲估计

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摘要

Focusing on densely deployed wireless sensor networks, this paper presents a novel method for joint source-channel-network coding of distributed correlated sources through multiple access relay channels. In such networks, the role of intermediate sensors as relay nodes permits to achieve enhanced end-to-end error performance and increased spatial diversity in presence of channel fading. This paper addresses this scenario for a two source, single relay architecture by proposing a novel coding approach based on concatenated Zigzag codes, whose low complexity is specially suitable for energy-constrained autonomous systems. Joint decoding and estimation of the parameters denning the correlation between sensors is iteratively performed at the receiver side. Simulation results show that the proposed joint coding scheme attains significant energy gains with respect to traditional routing techniques, specially at high signal to noise ratios.
机译:针对密集部署的无线传感器网络,本文提出了一种通过多个访问中继信道对分布式相关源进行联合源-信道-网络编码的新方法。在这样的网络中,中间传感器作为中继节点的作用允许在存在信道衰落的情况下实现增强的端到端错误性能和增加的空间分集。本文通过提出一种基于级联之字形编码的新颖编码方法,解决了这种两种源,单个中继体系结构的情况,该方法的低复杂度特别适合于能量受限的自治系统。在接收器侧迭代地执行联合解码和参数估计,以拒绝传感器之间的相关性。仿真结果表明,相对于传统路由技术,特别是在高信噪比的情况下,所提出的联合编码方案获得了显着的能量增益。

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