A prediction-based joint bandwidth allocation scheme for heterogeneous wireless networks

With advanced network technologies in recent years, people may connect with different types of networks anytime, anywhere. Since wireless network resource distribution is an important issue, we propose a user mobility prediction algorithm, which considers the coverage of different types of base stations and varied mobility of pedestrians, vehicles, and mass transportation. In addition, a novel bandwidth utilization optimization technique is employed in this work to allocate bandwidth more efficiently. Hybrid genetic algorithm, which combines Genetic Algorithm and the local search to improve the frequency of finding Pareto set, is adopted to realize the optimization problem. The performance of our algorithm is compared to two other state-of-the art approaches in the literature. The simulation results show that our algorithms can achieve desirable performance in terms of network utilization, throughput, and QoS quality in the heterogeneous wireless networks.