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Beam searching for mmWave networks with sub-6 GHz WiFi and inertial sensors inputs: An experimental study
Computer Networks ( IF 5.6 ) Pub Date : 2021-08-04 , DOI: 10.1016/j.comnet.2021.108344
Maurizio Rea 1, 2 , Domenico Giustiniano 2 , Pablo Jiménez Mateo 2, 3 , Yago Lizarribar 2, 3 , Joerg Widmer 2
Affiliation  

Beam training in dynamic millimeter-wave (mm-wave) networks with mobile devices is highly challenging as devices must scan a large angular domain to maintain alignment of their directional beams under mobility. In this work, we exploit the trend of multiple chipsets integrated in the same mobile device to study a set of non-mmwave input data that can be leveraged jointly to provide faster beam search and better data rate. We leverage these findings to introduce SLASH, an algorithm that adaptively narrows the sector search space and accelerates link establishment, link maintenance and handover between mm-wave devices. We experimentally evaluate SLASH with commodity hardware, including a 60 GHz testbed, commercial sub-6 GHz WiFi APs and smartphones. SLASH can increase the median data rate by more than 22% for link establishment and 25% for link maintenance with respect to prior work.



中文翻译:

具有 6 GHz 以下 WiFi 和惯性传感器输入的毫米波网络的波束搜索:一项实验研究

具有移动设备的动态毫米波 (mm-wave) 网络中的波束训练极具挑战性,因为设备必须扫描大的角域以在移动性下保持其定向波束的对齐。在这项工作中,我们利用多个芯片组集成在同一移动设备中的趋势来研究一组非毫米波输入数据,这些数据可以共同利用以提供更快的波束搜索和更好的数据速率。我们利用这些发现来介绍 SLASH,这是一种自适应缩小扇区搜索空间并加速毫米波设备之间的链路建立、链路维护和切换的算法。我们使用商用硬件(包括 60 GHz 测试台、商用 sub-6 GHz WiFi AP 和智能手机)对 SLASH 进行了实验评估。

更新日期:2021-08-26
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