Abstract
We propose a distributed radio access network selection method for heterogeneous wireless network environment, in which mobile terminals can adaptively and seamlessly handover among different wireless access technologies. Our algorithm optimizes fairness of radio resource usage without centralized computing on the network side. As a decentralized optimization scheme, we introduce the dynamics of the mutually connected neural network dynamics, whose energy function autonomously minimizes by distributed update of each neuron. Since the objective function of the fairness becomes a fourth-order function of the neurons’ states which cannot be optimized by the conventional Hopfield neural network, we apply a neural network model extended to higher-order mutual connections and energy functions. By numerical simulation, we confirm that the proposed algorithm can optimize fairness of the throughput by distributed and autonomous computation.
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Hasegawa, M. et al. (2009). Application of Higher Order Neural Network Dynamics to Distributed Radio Resource Usage Optimization of Cognitive Wireless Networks. In: Köppen, M., Kasabov, N., Coghill, G. (eds) Advances in Neuro-Information Processing. ICONIP 2008. Lecture Notes in Computer Science, vol 5506. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02490-0_104
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DOI: https://doi.org/10.1007/978-3-642-02490-0_104
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