Intelligent Transmission Power Allocation for Distributed Beamforming in Wireless Sensor Networks

Distributed beamforming can significantly improve the reliability of the link and the capacity and the coverage of wireless networks. Using a subset number of nodes from a network of sensors, they collectively transmit a common message to an intended destination. In distributed beamforming, the maxi...

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Bibliographic Details
Published in:International journal of distributed sensor networks 2015-01, Vol.2015 (6), p.510516
Main Authors: Chung, Sungmoon, Joe, Inwhee
Format: Article
Language:English
Subjects:
Allocations
Beamforming
Channel capacity
Channels
Communication
Computer engineering
Data communications
Engineering research
Information sharing
Methods
Multimedia
Networks
Remote sensors
Sensors
Wireless networks
Wireless sensor networks
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Summary:Distributed beamforming can significantly improve the reliability of the link and the capacity and the coverage of wireless networks. Using a subset number of nodes from a network of sensors, they collectively transmit a common message to an intended destination. In distributed beamforming, the maximum channel capacity could be changed according to the number of cooperating source nodes and the distance (between the average source nodes and destination). Therefore, the scheme is necessary to guarantee the required channel capacity. However, it is difficult to adapt the practical environment due to signal fading, interference, and low quality of sensor nodes in WSNs. Therefore, we studied about the channel characteristic and required transmission power according to the number of cooperating nodes and the distance theoretically to overcome these problems. As a result, we propose an Intelligent Transmission Power Allocation (ITPA) algorithm to guarantee the required channel capacity considering dynamic channel statement, the number of cooperating source nodes, and the distance between the average source nodes and destination with simplicity computation. In addition, ITPA distinguishes noise data (using an exponential weighted received power average) from the estimated original data. From that the system can satisfy requirements of the user without wasting power by itself.
ISSN:1550-1329
1550-1477
1550-1477
DOI:10.1155/2015/510516