基于遗传算法的延迟约束网络波束形成方法

Hao Guo, Behrooz Makki, T. Svensson
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引用次数: 18

摘要

本文研究了初始接入波束形成方案在发射天线和用户数量大但数量有限的情况下的性能。特别地,我们开发了一种使用遗传算法的高效波束形成方案。此外,考虑到毫米波通信特性和不同的度量,我们研究了天线/接收器数量、波束形成分辨率以及硬件损伤等各种参数对系统性能的影响。如图所示,我们提出的算法是通用的,因为它可以有效地应用于不同的信道模型、度量和波束形成方法。此外,我们的结果表明,所提出的方案可以达到(几乎)与基于穷举搜索的最优方法相同的端到端吞吐量,而实现复杂性要低得多。
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A genetic algorithm-based beamforming approach for delay-constrained networks
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.
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Keynote speaker Keynote speaker Ad-Hoc, Mobile, and Wireless Networks: 19th International Conference on Ad-Hoc Networks and Wireless, ADHOC-NOW 2020, Bari, Italy, October 19–21, 2020, Proceedings Retraction Note to: Mobility Aided Context-Aware Forwarding Approach for Destination-Less OppNets Ad-Hoc, Mobile, and Wireless Networks: 18th International Conference on Ad-Hoc Networks and Wireless, ADHOC-NOW 2019, Luxembourg, Luxembourg, October 1–3, 2019, Proceedings
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