多频段小区扩展中基于神经网络的偏移优化性能评价

Ryuya Sembo, N. Miki
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引用次数: 0

摘要

移动网络上的数据流量仍在增加。为了支持如此大的流量,额外的更高频率使用是一种很有前途的技术。网络需要仔细地将用户与基站和频段相关联,因为在这种部署中,用户可以连接多个基站和多个频段。为了有效地卸载用户,小区范围扩展(CRE)是有效的,偏移值可以通过神经网络(NN)进行优化。在本文中,我们评估了基于神经网络的偏置优化在CRE中的多频段性能。仿真结果表明,该算法在性能和用户反馈之间取得了良好的平衡。
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Performance Evaluation of Neural Network-based Offset Optimization in Cell Range Expansion for Multiple Frequency Bands
The amount of data traffic over the mobile network is still increasing. To support such large amount of traffic, additional higher frequency usage is one of the promising techniques. The network needs to carefully associate the users to the base stations and frequency bands, since users can connect multiple BSs and multiple frequency bands in such deployments. In order to offload the users effectively, the cell range expansion (CRE) is effective, and the offset values can be optimized by the neural network (NN). In the paper, we evaluate the performance of the NN-based offset optimization in CRE for multiple frequency bands. Simulation results show the good trade-off between the performance and the amount of feedback from the users.
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