Characterizing achievable rates in multi-hop wireless mesh networks with orthogonal channels
IEEE/ACM Transactions on Networking (TON)
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Fair Allocation of Subcarrier and Power in an OFDMA Wireless Mesh Network
IEEE Journal on Selected Areas in Communications
IEEE Transactions on Neural Networks
An architecture for next-generation radio access networks
IEEE Network: The Magazine of Global Internetworking
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This paper presents a novel method based on Hopfield Neural Networks (HNN) for Cross-layer Dynamical Resource Allocation in Orthogonal Frequency Division Multiple Access (OFDMA)-based Wireless Mesh Networks (WMN). The objective is to optimize the maximization of the system throughput using HNN under the conditions of the signal-to-interference-plus-noise ratio (SINR) constraint, power constraint and time delay constraint. The objective problem is simplified by dividing the bit-loading matrix into three matrixes. The simulation results show that HNN method can effectively solve optimization problems of resource allocation in such system, and it is more effective than the selected Greedy Algorithm (GA) method.