A hybrid optimization approach for suppressing sidelobe level and reducing transmission power in collaborative beamforming

被引:2
|
作者
Sun, Geng [1 ,2 ,3 ]
Zhao, Xiaohui [2 ]
Liang, Shuang [1 ]
Liu, Yanheng [1 ]
Zhan, Ying [4 ]
Leung, Victor C. M. [5 ]
机构
[1] Jilin Univ, Coll Comp Sci & Technol, Changchun, Peoples R China
[2] Jilin Univ, Coll Commun Engn, Changchun, Peoples R China
[3] Jilin Univ, Minist Educ, Key Lab Symbol Computat & Knowledge Engn, Changchun, Peoples R China
[4] Georgia Inst Technol, Sch Elect & Comp Engn, Atlanta, GA 30332 USA
[5] Univ British Columbia, Dept Elect & Comp Engn, Vancouver, BC, Canada
来源
2019 IEEE 90TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2019-FALL) | 2019年
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
wireless sensor networks; collaborative beamforming; sidelobe level; swarm intelligence optimization;
D O I
10.1109/vtcfall.2019.8891325
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Conventional collaborative beamforming with virtual node antenna array often results in high maximum sidelobe level (SLL) due to the unexpected node positions. In this paper, a hybrid optimization approach (HOA) for the SLL suppression and transmission power reduction is proposed. The proposed HOA organizes the node locations according to the concentric circular antenna array for location optimization. Then, a novel algorithm called variation particle chicken swarm optimization (VPCSO) is proposed to further optimize the transmission power weight of the selected array nodes. Simulations are conducted and the results show that the proposed location optimization approach is effective, and the maximum SLL of the beam patterns obtained by VPCSO is lower than that of other algorithms. Moreover, the overall transmission power weights obtained by the proposed VPCSO is the lowest among all the comparison methods.
引用
收藏
页数:6
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