Traffic characteristics based dynamic radio resource management in heterogeneous wireless networks

The traffic with tidal phenomenon in Heterogeneous Wireless Networks (HWNs) has radically increased the complexity of radio resource management and its performance analysis. In this paper, a Simplified Dynamic Hierarchy Resource Management (SDHRM) algorithm exploiting the resources dynamically and intelligently is proposed with the consideration of tidal traffic. In network-level resource allocation, the proposed algorithm first adopts wavelet neural network to forecast the traffic of each sub-area and then allocates the resources to those sub-areas to maximise the network utility. In connection-level network selection, based on the above resource allocation and the pre-defined QoS requirement, three typical network selection policies are provided to assign traffic flow to the most appropriate network. Furthermore, based on multidimensional Markov model, we analyse the performance of SDHRM in HWNs with heavy tailed traffic. Numerical results show that our theoretical values coincide with the simulation results and the SDHRM can improve the resource utilization.