Distributed self-optimization for efficient reconfiguration in overlapping heterogenous wireless access networks

A distributed network self-optimization algorithm is proposed in this paper to support the automation of network reconfiguration in overlapping heterogenous access networks. As a large number of reconfigurable network elements coexist heterogeneously and network condition changes dynamically, distributed self-optimization in such complex environments can bring high system performance with minimum operation expenditure but also great challenge. This is because both quick respondence to the environment variation and global coordination among the heterogeneous reconfigurations are highly desired at the same time. In the proposed algorithm, the distributed optimization problem is mapped into a Mixed Strategy Game. According to equilibrium-oriented Mixed Strategy, the operating parameters of every network element can be refined efficiently without suffering impact from the heterogeneous neighboring reconfiguration within overlapping area. Simulation results show that both system blocking probability and average session bandwidth can be significantly improved using the proposed algorithm.