Interference reduction and capacity improvement in collaborative beamforming networks via directivity optimization

摘要

Collaborative beamforming with finite number of collaborating nodes produces sidelobes that depend on the nodes' arrangement. Sidelobes cause interference when they occur at the directions of unintended receivers and thus reduce the transmission rate at these receivers. Peak sidelobe minimization does not effectively minimize the overall sidelobe of a beampattern formed by collaborative beamforming. Two main contributions are highlighted in this paper. First, we proposed a new fitness function based on directivity instead of the conventional peak sidelobe. Second, we applied the genetic algorithm (GA) to reduce the sidelobe in collaborative beamforming. This proposed solution is implemented without any feedback from the unintended receiver(s). In the light of reduced sidelobe, we recorded the resultant capacity and calculated its improvement. Results showing up to 14% of capacity improvement, proving the efficacy of the proposed methodologies: the GA and the new fitness function.