2019/02/11 by Sami Aldalahmeh, Aldalahmeh, Sami A., Saleh O. Al-Jazzar +7
Computer Science · #Distributed Sensor Networks and Detection Algorithms #Energy Efficient Wireless Sensor Networks #FOS: Electrical engineering #Signal Processing (eess.SP) #Target Tracking and Data Fusion in Sensor Networks #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1902.03990
openalex publication_date 2019/02/11 · openalex created_date 2022/07/29 · openalex updated_date 2026/07/28
In this paper we investigate fusion rules for distributed detection in large\nrandom clustered-wireless sensor networks (WSNs) with a three-tier hierarchy;\nthe sensor nodes (SNs), the cluster heads (CHs) and the fusion center (FC). The\nCHs collect the SNs' local decisions and relay them to the FC that then fuses\nthem to reach the ultimate decision. The SN-CH and the CH-FC channels suffer\nfrom additive white Gaussian noise (AWGN). In this context, we derive the\noptimal log-likelihood ratio (LLR) fusion rule, which turns out to be\nintractable. So, we develop a sub-optimal linear fusion rule (LFR) that weighs\nthe cluster's data according to both its local detection performance and the\nquality of the communication channels. In order to implement it, we propose an\napproximate maximum likelihood based LFR (LFR-aML), which estimates the\nrequired parameters for the LFR. We also derive Gaussian-tail upper bounds for\nthe detection and false alarms probabilities for the LFR. Furthermore, an\noptimal CH transmission power allocation strategy is developed by solving the\nKarush-Kuhn-Tucker (KKT) conditions for the related optimization problem.\nExtensive simulations show that the LFR attains a detection performance near to\nthat of the optimal LLR and confirms the validity of the proposed upper bounds.\nMoreover, when compared to equal power allocation, simulations show that our\nproposed power allocation strategy achieves a significant power saving at the\nexpense of a small reduction in the detection performance.\n