2017/10/26 by H. Ahmadi, Ahmadi, Hamid R., Nahal Maleki +3
Computer Science · Decision Sciences · #Advanced Statistical Process Monitoring #Distributed Sensor Networks and Detection Algorithms #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.1710.09540
openalex publication_date 2017/10/26 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
We consider a binary hypothesis testing problem in an inhomogeneous wireless\nsensor network, where a fusion center (FC) makes a global decision on the\nunderlying hypothesis. We assume sensors observations are correlated Gaussian\nand sensors are unaware of this correlation when making decisions. Sensors send\ntheir modulated decisions over fading channels, subject to individual and/or\ntotal transmit power constraints. For parallel-access channel (PAC) and\nmultiple-access channel (MAC) models, we derive modified deflection coefficient\n(MDC) of the test statistic at the FC with coherent reception.We propose a\ntransmit power allocation scheme, which maximizes MDC of the test statistic,\nunder three different sets of transmit power constraints: total power\nconstraint, individual and total power constraints, individual power\nconstraints only. When analytical solutions to our constrained optimization\nproblems are elusive, we discuss how these problems can be converted to convex\nones. We study how correlation among sensors observations, reliability of local\ndecisions, communication channel model and channel qualities and transmit power\nconstraints affect the reliability of the global decision and power allocation\nof inhomogeneous sensors.\n