Beam Selection Approach in Millimeter Wave Communication using Multi-Objective Prairie Dog Optimization

The selection of beam relies as a major conflict in wireless communication systems. The beam selection has been widely utilized in millimeter wave bands which helps to mitigate the path loss and minimize the energy consumption. The existing beam selection approaches results in high computational and communication costs and hinders the widespread deployment of mm Wave communications. Moreover, the existing approaches faced issues related to select the users for multiple radio frequencies and this suffers the users to face computational burden and results in beam optimization problem. So, this research utilized a Multi-Objective Prairie Dog Optimization (MOPDO) algorithm to perform an effective beam selection for multiple users in a single iteration. MOPDO considers the multiobjective functionalities such as beam power, energy efficiency, spectral efficiency and computational time. The experimental evaluation of proposed approach is evaluated with Alternative Grey Wolf with Beetle Swarm Optimization (AGW-BSO). For example, computational time of the proposed MOPDO is 320.87 seconds whereas the existing AGW-BSO is 355.72 seconds.