2017/11/30 by Mojtaba Shirazi, Shirazi, Mojtaba, Alireza Sani +3
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.1712.00122
openalex publication_date 2017/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we study the problem of distributed estimation of a Gaussian\nvector with linear observation model in a wireless sensor network (WSN)\nconsisting of K sensors that transmit their modulated quantized observations\nover orthogonal erroneous wireless channels (subject to fading and noise) to a\nfusion center, which estimates the unknown vector. Due to limited network\ntransmit power, only a subset of sensors can be active at each task period.\nHere, we formulate the problem of sensor selection and transmit power\nallocation that maximizes the trace of Bayesian Fisher Information Matrix (FIM)\nunder network transmit power constraint, and propose three algorithms to solve\nit. Simulation results demonstrate the superiority of these algorithms compared\nto the algorithm that uniformly allocates power among all sensors.\n