Paper Info
Title
Improving Performance of Distributed Collaborative Beamforming in Mobile Wireless Sensor Networks: A Multiobjective Optimization Method
Abstract
Mobile wireless sensor networks (MWSNs) are resource constrained, and have limited energy and transmission range. Distributed collaborative beamforming (DCB) in MWSNs based on a virtual node antenna array (VNAA) can increase the transmission distance and enhance the energy efficiency of a single sensor node. To achieve a lower maximum sidelobe level (SLL), sensor nodes can move to optimal locations with optimal excitation current weights for DCB. However, this leads to an extra motion energy consumption. In this article, we construct a multiobjective optimization framework (MOF) to jointly optimize the maximum SLL, transmission power, and motion energy consumption of the DCB nodes in MWSNs. Moreover, an improved nondominated sorting genetic algorithm-II (INSGA-II) and a distributed parallel INSGA-II (DPINSGA-II) are proposed for solving the formulated MOF. In addition, a simple but practical DCB scheduling mechanism is proposed. The simulation results show that the maximum SLL, transmission power, and motion energy consumption of the VNAA can be effectively optimized by the proposed algorithms.
Year
DOI
Venue
2020
10.1109/JIOT.2020.2983519
IEEE Internet of Things Journal
Keywords
DocType
Volume
Antenna arrays,collaborative beamforming,genetic algorithm (GA),mobile wireless sensor networks (MWSNs),multiobjective optimization
Journal
7
Issue
ISSN
Citations 
8
2327-4662
4
PageRank 
References 
Authors
0.41
0
8
Name
Order
Citations
PageRank
Geng Sun1199.77
Xiaohui Zhao2113.91
Guojun Shen340.75
Yanheng Liu422836.14
Aimin Wang581.50
S. Jayaprakasam6332.82
Ying Zhang73811.41
Victor C. M. Leung89717759.02