Opposition based Spider Monkey Optimization Algorithm for Load Balancing in LTE Network

At Present telecommunication is progressed due to the development of Long-Term Evolution (LTE) standard. This LTE network provides high-speed wireless communication for mobile devices and satisfies requirements of customers from multi-cells. However, due to the congestion of mobile devices, each cell in the network may get overloaded. So, load balancing is the main challenge to the LTE network for reducing congestion or load in the cell. For load balancing, optimal cell selection method is presented in this paper. Initially, load factor of each cell is estimated. The load factor is compared to the pre-defined threshold load value. After comparison, the high load cell handles users to the optimal cell or low load cell. This optimal cell has been selected with the Opposition-Based Spider Monkey Optimization Algorithm (OSMOA). Simulation results show that the proposed approach works better than previous methods in terms of call blocking rate (CBR) and call Dropping Ratio (CDR).