Adaptive Collaborative Beamforming in Wireless Sensor Network Based on Modified Backtracking Search Algorithm

Abstract

Collaborative beamforming (CB) in wireless sensor network (WSN) increases the transmission distance, which allow nodes to transmit data directly to the base station without relying on multi-hop transmissions. The choice of sensor node location directly affects the sidelobe levels of the radiation beampattern, which can affect the energy efficiency of the WSN. Therefore, an Artificial Intelligence algorithm, i.e. the Backtracking Search Algorithm (BSA) has been developed and implemented to optimize the radiation beampattern performance by finding the suitable location of the sensor nodes based on the linear array sensor nodes arrangement. The proposed Modified BSA-based Linear Array (LinearBSA) shows a superior improvement compared to the conventional linear array (LFA) in desired performance, i.e. minimize sidelobe level (SLL) and adaptive main beam angle. Performance on 8-, 12-and 16-node LinearBSA shows an improvement in radiation beampattern performance particularly in SLL minimization in any desired adaptive main beam angle.