论文标题

基于图的MMWave车辆网络中的光束管理模型

Graph-based Model for Beam Management in Mmwave Vehicular Networks

论文作者

Fazliu, Zana Limani, Chiasserini, Carla Fabiana, Malandrino, Francesco, Nordio, Alessandro

论文摘要

MMWave乐队被广泛吹捧为未来5G网络的非常有前途的选择,尤其是在使此类网络能够满足高度苛刻的利率要求时。因此,这些频段的使用也在5G车辆网络的背景下获得越来越多的兴趣,在这种情况下,预计连接的汽车很快将需要传输和接收大量数据。但是,MMWave通信需要使用狭窄的定向光束来建立链接,以克服恶劣的传播条件。使这可以在基站进行复杂的梁设计的高级天线系统,可以在其中设置多个宽度的多个光束。在这项工作中,我们使用基于图形的方法来建模系统特征和现有约束。特别是,与以前的工作不同,我们将光束设计问题作为与冲突的两部分图上的最大重量匹配问题,然后使用有效的启发式算法对其进行解决。我们的结果表明,我们的方法很容易根据聚类算法优于高级方法。

Mmwave bands are being widely touted as a very promising option for future 5G networks, especially in enabling such networks to meet highly demanding rate requirements. Accordingly, the usage of these bands is also receiving an increasing interest in the context of 5G vehicular networks, where it is expected that connected cars will soon need to transmit and receive large amounts of data. Mmwave communications, however, require the link to be established using narrow directed beams, to overcome harsh propagation conditions. The advanced antenna systems enabling this also allow for a complex beam design at the base station, where multiple beams of different widths can be set up. In this work, we focus on beam management in an urban vehicular network, using a graph-based approach to model the system characteristics and the existing constraints. In particular, unlike previous work, we formulate the beam design problem as a maximum-weight matching problem on a bipartite graph with conflicts, and then we solve it using an efficient heuristic algorithm. Our results show that our approach easily outperforms advanced methods based on clustering algorithms.

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