Design and Implementation of A Distributed Radio Resource Usage Optimization Algorithm for Heterogeneous Wireless Networks

We have designed and implemented a radio access network selection algorithm for heterogeneous wireless network environment, in which mobile terminals can adaptively and seamlessly handover among different radio access technologies. We propose a radio resource usage optimization algorithm without centralized computation on the network side, which is based on the Hopfield neural network dynamics whose energy function autonomously minimizes by distributed update of each neuron. We have implemented the proposed algorithm on an experimental heterogeneous wireless network system, which includes functionalities defined in IEEE 1900.4. First, we show that the proposed algorithm can optimize fairness of the throughput by numerical simulation. Then, we show that our algorithm works correctly and optimizes radio resource usage also on the experimental wireless network by distributed handover decisions on the terminal side.