Summary
2011 International Symposium on Nonlinear Theory and Its Applications
2011
Session Number:A1L-B
Session:
Number:A1L-B2
Self-Optimized Wireless Distributed Networks
Mikio Hasegawa,
pp.25-28
Publication Date:2011/9/4
Online ISSN:2188-5079
Summary:
Distributed optimization dynamics of the mutually connected neural networks is applied to radio resource usage optimization in heterogeneous type cognitive radio networks. For performance evaluation, the proposed algorithm is implemented on an experimental heterogeneous wireless network system called Cognitive Wireless Cloud, which supports vertical handover between different radio access networks and various information exchange defined in IEEE1900.4. The proposed cognitive radio system optimizes objective function without any centralized computation. As the objective functions, two types of problems are introduced, load balancing and QoS satisfaction rate optimization, and the performance of the proposed method is compared with other distributed RAN selection algorithms on the real wireless system. Since the proposed algorithm based on the neural network dynamics directly optimizes the objective functions defined for radio resource usage optimization of the entire wireless network by distributed computation on each terminal, its performance becomes better than other algorithm which is based on the improvement of each terminal’s QoS.