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User bandwidth usage-driven hnn neuron excitation method for maximum resource utilization within packet-switched communication networks

机译:用户带宽使用量驱动的hnn神经元激励方法,在分组交换通信网络中实现最大的资源利用率

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摘要

Mobile and wireless systems beyond 3G are being designed under the user-centric paradigm. Dynamic resource allocation (DRA) is a topic on intensive research to address efficiently such paradigm. Hopfield neural networks (HNN) have proved useful in the past to solve this kind of complex optimization problems. Recently, various approaches have been proposed to realize HNN-based user-centric DRA. However, the initial algorithms suffer from severe instability problems impacting the overall performance. This letter analyses the source of the existing limitations and proposes an enhanced formulation, ensuring maximum resource utilization while optimizing the convergence of the neural network. The letter highlights the improved performance in terms of optimum convergence and bandwidth utilization
机译:3G以外的移动和无线系统正在以用户为中心的范式下进行设计。动态资源分配(DRA)是有关深入研究的主题,以有效地解决此类问题。过去,Hopfield神经网络(HNN)已证明对解决这类复杂的优化问题很有用。近来,已经提出了各种方法来实现基于HNN的以用户为中心的DRA。但是,初始算法存在严重的不稳定问题,影响了整体性能。这封信分析了现有局限性的根源,并提出了一种改进的方案,以确保最大程度地利用资源,同时优化神经网络的收敛性。这封信强调了最佳融合和带宽利用率方面的改进性能

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