MH-SIA: multi-objective handover using swarm intelligence algorithm for future wireless communication system

Heterogeneous networks are needed to meet user demands as wireless network demand rises. Network mobility management is crucial. Mobility management challenges are related to handover solutions to decrease call/packet losses in such networks. The handover is one of the most critical parts of mobility management in the Long-Term Evolution of Advanced (LTE-A) system, which relies on handover procedures to improve quality, coverage, and service in the existing network. The LTE-A future wireless communication networks consist of various femtocells, microcells, and macrocells. Therefore, designing the appropriate mechanism to perform handovers among different cells is a challenging research problem. We propose a novel handover mechanism called multi-objective handover using swarm intelligence algorithm (MH-SIA) for the future wireless communication system. MH-SIA is made of two novel features multi-objective handover and SIA for handover process optimization. The multi-objective trust parameters of each User's Equipment are computed to perform the handover decision-making and target cell selection using the SIA. The computed trust parameters are utilized as the modified fitness function in Differential Evolution (DE) optimization technique. Due to the fast convergence of DE, it performs computationally efficient handover operations. The multi-objective trust parameters are utilized in handover decision-making and target cell selection to improve network performances with minimum handover latency. The experimental result of MH-SIA reveals the efficient performance compared to underlying methods.