Genetic Based Approach to Optimize the Vertical Handover Performance Among Heterogeneous Network

Abstract

Mobile terminals typically can be connected to multiple wireless networks that offer different degrees of suitability for different classes of service. A genetic algorithm (GA) - based on a supervised approach - is used to assess the likelihood of a successful handover in heterogeneous networks to increase capacity and network performance. Traditional handoff schemes are prone to ping-pong and corner effects, and the development of an optimized handover scheme for a seamless, faster and less energy-consuming handover decision is a challenge. In order to ensure service continuity and to maintain the promising QoS, the handover decision should be made appropriately. The most general criteria for handover is the received signal strength, which is not sufficient in advanced networks. The GA scheme can effectively optimize the soft handoff decision by using the best-fit network for the mobile terminal (MT), taking into account the quality of service requirements (QoS), the network parameters, and the user preference for the cost of the various connection points for the MT is selected. The mathematical model-based approach to vertical handoff prediction involves a well-defined objective function taking into account signal strength, user equipment speed, load and cost per user bandwidth. The system performance can be improved according to the user settings by adjusting the weights in the defined objective function. Due to the high bandwidth and easy networking, the system consider the wireless access standards: UMTS, Wi-Fi, LTE and Wimax. The decision problem is formulated as several objective optimization problems and simulated using a monitored genetic algorithm. The simulation result shows that the number of handovers can be minimized when using optimized network parameter values.