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A genetic algorithm-based beamforming approach for delay-constrained networks

机译:一种基于遗传算法的延迟约束网络波束形成方法

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In this paper, we study the performance of initial access beamforming schemes in the cases with large but finite number of transmit antennas and users. Particularly, we develop an efficient beamforming scheme using genetic algorithms. Moreover, taking the millimeter wave communication characteristics and different metrics into account, we investigate the effect of various parameters such as number of antennas/receivers, beamforming resolution as well as hardware impairments on the system performance. As shown, our proposed algorithm is generic in the sense that it can be effectively applied with different channel models, metrics and beamforming methods. Also, our results indicate that the proposed scheme can reach (almost) the same end-to-end throughput as the exhaustive search-based optimal approach with considerably less implementation complexity.
机译:在本文中,我们研究了大而是有限数量的发射天线和用户的情况下初始访问波束形成方案的性能。特别是,我们使用遗传算法开发一种有效的波束形成方案。此外,考虑到毫米波通信特性和不同的指标,我们研究了各种参数,例如天线/接收器,波束形成分辨率以及系统性能的硬件损伤的影响。如图所示,我们所提出的算法是通用的,即它可以有效地应用于不同的信道模型,度量和波束成形方法。此外,我们的结果表明,所提出的方案可以达到(几乎)与以穷举的搜索的最优方法相同的端到端吞吐量,其实现复杂性相当较少。

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