A Sidelobe and Energy Optimization Array Node Selection Algorithm for Collaborative Beamforming in Wireless Sensor Networks

作者：Sun, Geng; Liu, Yanheng; Liang, Shuang; Chen, Zhaoyu; Wang, Aimin^*; Ju, Qianao; Zhang, Ying^*

来源：IEEE Access, 2018, 6: 2515-2530.

DOI：10.1109/ACCESS.2017.2783969

• Wireless sensor networks
• random antenna arrays
• cuckoo algorithm
• energy efficient
• beamforming

The beam pattern of the virtual node antenna array (VNAA) in wireless sensor networks has a high maximum sidelobe level (SLL), thereby causing communication interference because of the uncontrollable node positions. A sidelobe and energy optimization array node selection (SEOANS) algorithm is proposed for optimally selecting the sensor nodes to form a VNAA that optimizes the beam pattern of VNAA and reduces the average energy consumption of nodes. SEOANS uses a calculation method to determine the optimal number of array nodes, proposes a node location selection optimization method based on concentric circular ring array and a novel swarm intelligence optimization algorithm called cuckoo search chicken swarm optimization (CSCSO) to optimize the excitation current of each array node. CSCSO uses chaos theory, introduces the inertia weight Levy flight, and adopts the grade mechanism in chicken swarm optimization to improve the performance of the cuckoo search algorithm. In addition, the scheduling and fault tolerance mechanisms are designed and implemented in SEOANS. Simulation results show that the node position selection optimization method and the excitation current optimization based on CSCSO can effectively reduce the maximum SLL. Furthermore, compared with traditional clustering routing algorithms, SEOANS has advantages in the communication delay and average energy consumption of nodes, thus effectively improving network lifetime.

• 出版日期2018
• 单位吉林大学