2015/08/31 by Nahal Maleki, Maleki, Nahal, Azadeh Vosoughi +3
Computer Science · Engineering · #Distributed Sensor Networks and Detection Algorithms #FOS: Computer and information sciences #Information Theory (cs.IT) #Wireless Communication Security Techniques
paper · pdf · doi:10.48550/arxiv.1508.07913
openalex publication_date 2015/08/31 · openalex created_date 2022/10/05 · openalex updated_date 2026/07/28
This paper considers the problem of binary distributed detection of a known\nsignal in correlated Gaussian sensing noise in a wireless sensor network, where\nthe sensors are restricted to use likelihood ratio test (LRT), and communicate\nwith the fusion center (FC) over bandwidth-constrained channels that are\nsubject to fading and noise. To mitigate the deteriorating effect of fading\nencountered in the conventional parallel fusion architecture, in which the\nsensors directly communicate with the FC, we propose new fusion architectures\nthat enhance the detection performance, via harvesting cooperative gain\n(so-called decision diversity gain). In particular, we propose: (i) cooperative\nfusion architecture with Alamouti's space-time coding (STC) scheme at sensors,\n(ii) cooperative fusion architecture with signal fusion at sensors, and (iii)\nparallel fusion architecture with local threshold changing at sensors. For\nthese schemes, we derive the LRT and majority fusion rules at the FC, and\nprovide upper bounds on the average error probabilities for homogeneous\nsensors, subject to uncorrelated Gaussian sensing noise, in terms of\nsignal-to-noise ratio (SNR) of communication and sensing channels. Our\nsimulation results indicate that, when the FC employs the LRT rule, unless for\nlow communication SNR and moderate/high sensing SNR, performance improvement is\nfeasible with the new fusion architectures. When the FC utilizes the majority\nrule, such improvement is possible, unless for high sensing SNR.\n