Multi-objective optimization for distributed collaborative beamforming in mobile wireless sensor networks

Sun, Geng; Liu, Yanheng; Shen, Guojun; Zhang, Ying; Leung, Victor C. M.

doi:10.1109/iscc.2018.8538536

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Mobile WSN is also equipped with antenna and limited power resource. Thus, due to the mobility of MWSN, long distance communication between sensor nodes and base station is impossible through multi-hop communication as it can increase motion energy and transmission power as well as communication delay [21]. As a solution, MWSN can form a VAA to perform CB.…”

Section: Mobile Wireless Sensor Networkmentioning

confidence: 99%

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Beampattern optimization techniques using metaheuristic algorithm for collaborative beamforming: a review

2023

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The fast improvements in wireless technology and embedded systems have sparked a renewed interest in collaborative beamforming (CB) approach used in wireless sensor networks (WSNs). Despite the fact that studies on distributed and CB have been conducted for more than 10 years, CB was previously deemed unworkable because of its extreme complexity and difficult-to-attain criteria. It just got well-known in the last several years when cheaply accessible compact wireless communication electronic sensors with high processing capability emerged. These factors contributed as the motivation for this paper's research overview CB in WSNs. We provide the classifications of the static and mobile WSN which is based on the sensor node optimization technique. This paper reviews the metaheuristic algorithms proposed by previous study for beampattern and energy consumption optimization. Finally, this paper also presents a summary analysis of the previous studies in terms of beampattern characteristic and properties, energy consumption and stability.

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Section: Mobile Wireless Sensor Networkmentioning

confidence: 99%

“…Besides, Sun et al [21] proposed a multi-objective optimization framework (MOF) to jointly reduce SLL, increase transmission rate and reduce motion energy by optimizing location and excitation current of MWSN. Improved non-dominated sorting GA (INSGA-II) is introduced in MOF to improve computer efficiency and accuracy.…”

Section: Mobile Wireless Sensor Networkmentioning

confidence: 99%