Optimal Local Thresholds for Distributed Detection in Energy Harvesting Wireless Sensor Networks
Optimal Local Thresholds for Distributed Detection in Energy Harvesting Wireless Sensor Networks
复制标题
能量收集无线传感器网络中分布式检测的最佳局部阈值
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
A. Vosoughi
中科院分区：
文献类型：
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作者：
Ghazaleh Ardeshiri;H. Yazdani;A. Vosoughi
我们考虑一个由Κ异质传感器和一个融合中心(FC)组成的无线传感器网络，其任务是解决一个二进制分布式检测问题。每个传感器都能够收集和存储能量，以便与FC进行通信。为了提高能效，传感器仅在传感器测试统计数据超过本地阈值θk、其信道增益超过最小阈值、且其电池状态能够承受传输时才进行传输。我们提出的每个传感器处的传输模型是受无线通信社区中的信道反向功率控制策略的激励。考虑到发射符号平均能量的约束，我们研究了优化两个检测性能指标的最优θk：(I)在FC处的检测概率Pd，假设FC使用基于Neyman-Pearson最优准则的最优融合规则；(Ii)在FC处接收信号的两个分布之间的K-L距离(KL)在每个假设条件下。我们的数值结果表明，通过最大化KL距离得到的θk是接近最优的。找到这些阈值在计算上是高效的，因为它只需要Κ一维搜索，而不是找到最大化PD的阈值所需的K维搜索。
We consider a wireless sensor network, consisting of Κ heterogeneous sensors and a fusion center (FC), that is tasked with solving a binary distributed detection problem. Each sensor is capable of harvesting and storing energy for communication with the FC. For energy efficiency, a sensor transmits only if the sensor test statistic exceeds a local threshold θk, its channel gain exceeds a minimum threshold, and its battery state can afford the transmission. Our proposed transmission model at each sensor is motivated by the channel inversion power control strategy in the wireless communication community. Considering a constraint on the average energy of transmit symbols, we study the optimal θk's that optimize two detection performance metrics: (i) the detection probability PD at the FC, assuming that the FC utilizes the optimal fusion rule based on Neyman-Pearson optimality criterion, and (ii) Kullback-Leibler distance (KL) between the two distributions of the received signals at the FC conditioned by each hypothesis. Our numerical results indicate that θk's obtained from maximizing the KL distance are near-optimal. Finding these thresholds is computationally efficient, as it requires only Κ one-dimensional searches, as opposed to a K-dimensional search required to find the thresholds that maximize PD.