An Experimental Study of Rate and Beam Adaptation in 60 GHz WLANs

An Experimental Study of Rate and Beam Adaptation in 60 GHz WLANs
复制标题

60 GHz WLAN 中速率和波束自适应的实验研究

DOI:
10.1145/3416010.3423219
复制
发表时间:
2020
期刊:
Analysis and Simulation of Wireless and Mobile Systems
影响因子:
--
通讯作者:
Koutsonikolas, Dimitrios
Koutsonikolas, Dimitrios
中科院分区:
--
文献类型:
--
作者:
Aggarwal, Shivang;Sardesai, Urjit Satish;Sinha, Viral;Koutsonikolas, Dimitrios

文献摘要

参考文献

相似文献

在本文中,我们利用从60 GHz软件定义无线电试验台收集的大量数据集,对60 GHz无线局域网中的两种主要链路自适应机制(即速率自适应和波束自适应)进行了广泛的实验研究。首先,我们比较了两种机制在各种室内环境和场景中的有效性,包括线性和角位移、流动性、阻塞和干扰。接下来,我们研究了两种速率自适应方法的有效性——基于信噪比的速率自适应方法,这是由最近的研究提出的,以及基于学习的使用物理层信息的方法。我们的研究结果表明,前者在实际场景中表现不佳,而后者则很有希望,特别是与在线培训相结合时。最后,我们探讨了保持备份波束以加速链路恢复和减少波束训练开销的有效性。我们表明,这种启发式在涉及接收方角位移的情况下失败,但在大多数其他情况下是相当有效的。
In this paper, we conduct an extensive experimental study of the two primary link adaptation mechanisms in 60 GHz WLANs, namely rate adaptation and beam adaptation, using a large data set collected from a 60 GHz software-defined radio testbed. First, we compare the effectiveness of the two mechanisms in a variety of indoor environments and scenarios, including linear and angular displacement, mobility, blockage, and interference. Next, we study the effectiveness of two rate adaptation approaches -- SNR-based rate adaptation, which has been proposed by recent works, and a learning-based approach using PHY layer information. Our results show that the former performs poorly in practical scenarios, while the latter is promising, especially when combined with online training. Finally, we explore the effectiveness of maintaining backup beams to speedup link recovery and reduce the beam training overhead. We show that this heuristic fails in scenarios involving angular displacement on the receiver side but is quite effective in most other scenarios.
DOI: 10.1002/bltj.2069
发表时间: 1997-06-01
影响因子: --
作者:
Kamerman, A;Monteban, L
通讯作者: Monteban, L
DOI: 10.1109/icccn.2019.8847085
发表时间: 2019-07
期刊: 2019 28th International Conference on Computer Communication and Networks (ICCCN)
影响因子: --
作者:
Ding Zhang;P. Santhalingam;Parth H. Pathak;Zizhan Zheng
通讯作者: Ding Zhang;P. Santhalingam;Parth H. Pathak;Zizhan Zheng
DOI: 10.1145/3230543.3230581
发表时间: 2018-08
期刊: Proceedings of the 2018 Conference of the ACM Special Interest Group on Data Communication
影响因子: --
作者:
Haitham Hassanieh;Omid Salehi-Abari;Michael Rodriguez;M. Abdelghany;D. Katabi;P. Indyk
通讯作者: Haitham Hassanieh;Omid Salehi-Abari;Michael Rodriguez;M. Abdelghany;D. Katabi;P. Indyk
DOI: 10.1145/2716281.2836102
发表时间: 2015-12
期刊: Proceedings of the 11th ACM Conference on Emerging Networking Experiments and Technologies
影响因子: --
作者:
Thomas Nitsche;Guillermo Bielsa;Irene Tejado;Adrian Loch;J. Widmer
通讯作者: Thomas Nitsche;Guillermo Bielsa;Irene Tejado;Adrian Loch;J. Widmer