Over-the-Air Multisensor Collaboration for Resource Efficient Joint Detection
Over-the-Air Multisensor Collaboration for Resource Efficient Joint Detection
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DOI：
10.1109/tsp.2023.3310895
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发表时间：
2024
影响因子：
5.4
通讯作者：
Carlos Feres;B. Levy;Zhi Ding
中科院分区：
文献类型：
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作者：
Carlos Feres;B. Levy;Zhi Ding
我们通过提出一种新的空中软信息聚合，开发了分布式传感器网络协同决策的资源高效框架。我们利用无线传输的自然叠加，使传感器能够利用空中计算来近似充分的统计量，以便在共享信道上进行最佳检测。通过在空中计算中设计实用的发送和接收处理，决策融合中心可以在低失真的情况下，以无线方式获得所有观测数据计算的总对数似然比的良好近似值。在这个新框架中，我们开发了有效的测试，并分析了它们在几种常见的联合检测场景中的性能界限。我们的研究结果显示，即使只有几个参与的传感器，也可以获得显著的无线协作增益。尽管通过空中计算节省了大量资源，但新框架在检测节点的传统多址传输中表现出很小的检测精度性能损失。
We develop a resource-efficient framework for collaborative decision-making over distributed sensor networks by proposing a novel over-the-air soft information aggregation. We exploit the natural superposition of wireless transmissions to enable sensors to utilize over-the-air computation to approximate the sufficient statistic for optimum detection over a shared channel. By designing practical transmission and receiver processing in over-the-air computation, the decision-making fusion center can wirelessly obtain a good approximation of the aggregate log-likelihood ratio computed over all observed data with low distortion. Focusing on Neyman-Pearson tests for detection in this new framework, we develop efficient tests and analyze their performance bounds in several common joint detection scenarios. Our results show significant over-the-air collaboration gain even with a few participating sensors. The novel framework exhibits very little performance loss of detection accuracy against traditional multiple access transmission from sensing nodes despite substantial resource savings via over-the-air computation.