Continuous-time Hopfield neural network-based optimized solution to 2-channel allocation problem

Authors : Zekeriya UYKAN

Pages : 480-490

Doi:10.3906/elk-1212-148

View : 18 | Download : 9

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :The channel allocation problem in cellular radio systems is NP-complete, and thus its general solution is not known for even the 2-channel case. It is well known that the link gain system matrix insert ignore into journalissuearticles values(or received-signal power system matrix); of the radio network is insert ignore into journalissuearticles values(and may be highly); asymmetric, and that as the Hopfield neural network is applied to optimization problems, its weight matrix should be symmetric. The main contribution of this paper is as follows: turning the channel allocation problem into a maxCut graph partitioning problem, we propose a simple and effective continuous-time Hopfield neural network-based solution by determining its symmetric weight matrix from the asymmetric received-signal-power-system matrix. Computer simulations confirm the effectiveness and superiority of the proposed solution as compared to standard algorithms for various illustrative cellular radio scenarios for the 2-channel case.
Keywords : Continuous time Hopfield neural network, maxCut problem, channel allocation problem