论文标题
基于混合模型和数据驱动的MMWave蜂窝网络中频谱共享的方法
A Hybrid Model-based and Data-driven Approach to Spectrum Sharing in mmWave Cellular Networks
论文作者
论文摘要
毫米波带中的操作频谱共享具有大大增加频谱利用率,并为单个用户设备提供更大的带宽,以增加操作员的干扰。不幸的是,传统的基于模型的频谱共享方案在延迟和协议开销方面对操作员间协调机制做出了理想主义的假设,同时对缺少的通道状态信息敏感。在本文中,我们提出了基于混合模型和数据驱动的多手术器频谱共享机制,该机制结合了基于模型的波束形成和用户关联,并由数据驱动的模型修补汇编。我们的解决方案具有与基于模型的方法相同的计算复杂性,但其主要优点是信号开销大大降低。我们讨论有限的渠道状态信息和量化基于密码的光束形成如何影响学习和频谱共享性能。我们表明,提出的混合共享方案显着改善了在操作员协调和渠道状态信息获取的现实假设下的频谱利用率。
Inter-operator spectrum sharing in millimeter-wave bands has the potential of substantially increasing the spectrum utilization and providing a larger bandwidth to individual user equipment at the expense of increasing inter-operator interference. Unfortunately, traditional model-based spectrum sharing schemes make idealistic assumptions about inter-operator coordination mechanisms in terms of latency and protocol overhead, while being sensitive to missing channel state information. In this paper, we propose hybrid model-based and data-driven multi-operator spectrum sharing mechanisms, which incorporate model-based beamforming and user association complemented by data-driven model refinements. Our solution has the same computational complexity as a model-based approach but has the major advantage of having substantially less signaling overhead. We discuss how limited channel state information and quantized codebook-based beamforming affect the learning and the spectrum sharing performance. We show that the proposed hybrid sharing scheme significantly improves spectrum utilization under realistic assumptions on inter-operator coordination and channel state information acquisition.