Sidelobe reduction and capacity improvement of open-loop collaborative beamforming in wireless sensor networks

Area of Science:

• Wireless communication
• Signal processing
• Optimization algorithms

Background:

• Collaborative beamforming (CBF) uses multiple collaborating nodes (CNs) to form beams.
• Sidelobes in CBF cause interference for unintended receivers, impacting communication rates.
• Open-loop CBF cannot null interference due to lack of receiver feedback.

Purpose of the Study:

• To analyze the effect of peak sidelobe (PSL) reduction in CBF on unintended receiver capacity.
• To investigate the relationship between sidelobe reduction and capacity improvement.
• To evaluate meta-heuristic optimization methods for PSL minimization.

Main Methods:

• Applied three meta-heuristic optimization methods: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Weightless Swarm Algorithm (WSA).
• Focused on minimizing the Peak Sidelobe Level (PSL) in CBF.
• Analyzed the resulting capacity changes for unintended receivers.

Main Results:

• Achieved an average reduction of 20 dB in PSL.
• Demonstrated up to 162% capacity improvement for unintended receivers in worst-case scenarios using WSA.
• Identified that PSL minimization benefits unintended receiver capacity only for small and dense CBF clusters.

Conclusions:

• PSL reduction in CBF is a viable strategy to mitigate interference and enhance unintended receiver capacity.
• The WSA optimization method proved effective for significant PSL reduction and capacity improvement.
• The effectiveness of PSL minimization for capacity enhancement is contingent on the CBF cluster's size and density.