A maximum channel reuse scheme with Hopfield Neural Network based static cellular radio channel allocation systems

In recent years, wireless and mobile communication systems become increasingly popular. The demand for mobile communication has thus made the industry put more efforts towards designing new-generation systems. One of the important issues in mobile-phone communications is about the static channel assignment problem (SCAP). Although many techniques have been proposed for SCAP, a challenge for the cellular radio communication system is how to enhance and maximize the frequency reuse. The general SCAP is known as an NP-hard problem. The static channel assignment scheme based on the Hopfield neural network was shown to perform well when compared to some other schemes such as graph coloring and genetic algorithm (GA). In this paper, we extend Kim et al.psilas modified Hopfield neural network methods and focus on channel reusing to obtain a near-optimum solution for CAP. Several constraints are considered for obtaining the desired results. Eight-benchmark problems are simulated and the energy evolution process is discussed. Simulation results demonstrated that the proposed scheme could make higher channel reuse rate.