Throughput Analysis and Optimization Based on Mobility Analysis and Markov Process for Heterogeneous Wireless Networks

One of the hot issues in heterogeneous wireless networks (HWNs) is radio resource utilization. The objective of this paper is to solve this problem. By considering the diversity of radio access technologies (RATs) in HWNs, the differences between them should be studied and exploited, e.g., coverage radius of each network, service arrival rate of each region, data transmission rate. The paper proposes a novel method for HWNs throughput analysis and optimization on the basis of these differences. Users engaging in calls in overlapping regions need to conduct network selection. To enhance the throughput of HWNs, users in these regions should be reasonably allocated to each network. Hence, the users’ proportion accessing each network is an important factor in the HWNs utilization. The mean total throughput of HWNs can be formulated by the Markov Model, which is determined by the distribution of service arrival rate and the analysis of handoff rate. Users’ mobility, furthermore, is important in network analysis because of its effect upon the handoff rate, which is one of the parameters to decide the throughput of HWNs. The service access proportion should be optimized to maximize the throughput of HWNs. By considering the convexity of the objective function, the subgradient method is employed in the solution of the optimization problem. Meanwhile, quadratic programming is used to reduce the computational complexity. Finally, a throughput optimization algorithm is proposed for HWNs on the basis of the architecture of common radio resource management, which can jointly manage diverse RATs. Then the validity of the proposed algorithm is illustrated through the simulation results, from which the paper simultaneously draw some important conclusions.