Distributed decision fusion in the presence of networking delays and channel errors
Information Sciences: an International Journal
A method for discrete stochastic optimization
Management Science
Accelerating the convergence of random search methods for discrete stochastic optimization
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation
Adaptive MIMO antenna selection via discrete stochastic optimization
IEEE Transactions on Signal Processing
IEEE Transactions on Information Theory
IEEE Communications Magazine
Distributed fault-tolerant classification in wireless sensor networks
IEEE Journal on Selected Areas in Communications
A survey of communication/networking in Smart Grids
Future Generation Computer Systems
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The basic idea of distributed detection is to have a number of independent sensors, each to make a local decision (typically a binary one) and then to combine their decisions at a fusion centre to make a global decision. Fault-tolerance has been considered as one of the main characteristics of wireless sensor networks. A fusion rule in the form of an error correction code has been recently proposed for better fault-tolerance in distributed sensor networks. In this paper, we propose to employ the powerful discrete stochastic approximation techniques to optimise the code matrix, that is, the fusion rule, with the objective of minimising the probability of decision error. We consider both the standard stochastic approximation algorithm and two newly proposed ones for this application. Extensive simulation results are provided to demonstrate the effectiveness of the proposed design paradigm in obtaining optimal fusion rules in distributed wireless sensor networks.