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J‐divergence‐based Power Allocation in Wireless Sensor Networks with Distributed Detection under Correlated Noises
Author(s) -
Mohajeran Seyed Ali,
Abed Hodtani Ghosheh
Publication year - 2020
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4459
Subject(s) - fusion center , computer science , divergence (linguistics) , wireless sensor network , channel (broadcasting) , fading , transmitter power output , binary number , power (physics) , wireless , mathematical optimization , constraint (computer aided design) , wireless network , mean squared error , algorithm , telecommunications , computer network , mathematics , statistics , cognitive radio , linguistics , philosophy , transmitter , arithmetic , physics , geometry , quantum mechanics
Summary In this paper, the power allocation problem in a wireless sensor network (WSN) with binary distributed detection is considered. It is assumed that the sensors independently transmit their local decisions to a fusion center (FC) through a slow fading orthogonal multiple access channel (OMAC), where, in every channel, the interferences from other devices are considered as correlated noises. In this channel, the associated power allocation optimization problem with equal power constraint is established between statistical distributions under different hypotheses by using the Jeffrey divergence (J‐divergence) as a performance criterion. It is shown that this criterion for the power allocation problem is more efficient compared to other criteria such as mean square error (MSE). Moreover, several numerical simulations and examples are presented to illustrate the effectiveness of the proposed approach.