Heterogeneous Network Selection Optimization Algorithm Based on a Markov Decision Model

A network selection optimization algorithm based on the Markov decision process (MDP) is proposed so that mobile terminals can always connect to the best wireless network in a heterogeneous network environment. Considering the different types of service requirements, the MDP model and its reward function are constructed based on the quality of service (QoS) attribute parameters of the mobile users, and the network attribute weights are calculated by using the analytic hierarchy process (AHP). The network handoff decision condition is designed according to the different types of user services and the time-varying characteristics of the network, and the MDP model is solved by using the genetic algorithm and simulated annealing (GA-SA), thus, users can seamlessly switch to the network with the best long-term expected reward value. Simulation results show that the proposed algorithm has good convergence performance, and can guarantee that users with different service types will obtain satisfactory expected total reward values and have low numbers of network handoffs.