Abstract:

Aiming at solving the problem that access selection method based on fuzzy logic and neural network technology for heterogeneous wireless network did not consider network load conditions reasonably, a particle swarm optimization (PSO)fuzzy neuron based access selection algorithm with dynamic adaptability for network load is proposed. This method set equal access blocking rate as a goal for fuzzy neuron parameter learning, and combined with PSO algorithm with global optimization capability to set initial parameters value, so as to improve the precision of parameter learning. Simulations show that the proposed algorithm can balance the load among networks effectively, and reduce the access blocking rate compared with maximum load balance algorithm.

Key words: heterogeneous wireless networks, access selection, fuzzy neuron, particle swarm optimization, load balance