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Neural network-based dynamic channel assignment for cellular mobile communication systems

机译:蜂窝移动通信系统的基于神经网络的动态信道分配

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摘要

Conventional dynamic channel assignment schemes are both time-consuming and algorithmically complex. An alternative approach, based on cascaded multilayered feedforward neural networks, is proposed and examined on two cellular systems with different configurations. Simulation results showed that the blocking performance of our multistage neural network approach can match that of an example conventional scheme with less complexity and higher computational efficiency. The example scheme considered here is the ordered channel search, which can achieve a reasonably high spectral efficiency as compared to that of an ideal dynamic channel allocation algorithm. We conclude that our neural network approach is well-suited to the dynamic channel allocation problem of future cellular or microcellular systems with decentralized control.
机译:常规的动态信道分配方案既费时又算法复杂。提出了一种基于级联多层前馈神经网络的替代方法,并在具有不同配置的两个蜂窝系统上进行了研究。仿真结果表明,我们的多级神经网络方法的阻塞性能可以与示例传统方案的阻塞性能相匹配,并且复杂度更低,计算效率更高。这里考虑的示例方案是有序信道搜索,与理想的动态信道分配算法相比,它可以实现合理高的频谱效率。我们得出的结论是,我们的神经网络方法非常适合于具有分散控制的未来蜂窝或微蜂窝系统的动态信道分配问题。

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