An Optimization Method for Load Balancing in Long Term Evaluation Self Optimization Network using Hybridized Bat Algorithm

Load balancing (LB) is an important use case in long-term evaluation (LTE) self-optimizing networks (SONs). To overcome the potential Ping-Pong load transfer and low-convergence issues, we propose a hand over optimization in LTE son to solve the asymmetry traffic distribution among multiple cells and delay. The Multi objective bat method along with priori expert knowledge reduces the search space and computation time. In PSO each particle (distortion types) flies in the search space with a velocity adjusted by its own flying memory and its companion’s flying experience. Each particle (distortion types) has its objective function value which is decided by a fitness function. The PSO process stops once the termination criteria have been satisfied. The proposed algorithm of hybridized bat algorithm combines both the Multi objective bat algorithm and PSO which reduces the number of iterations and produces the fitness solutions in short time.