Z. Khan, J. J. Lehtomäki, V. Selis, H. Ahmadi and A. Marshall, "Intelligent Autonomous User Discovery and Link Maintenance for mmWave and TeraHertz Devices With Directional Antennas," in IEEE Transactions on Cognitive Communications and Networking, vol. 7, no. 4, pp. 1200-1215, Dec. 2021, doi: 10.1109/TCCN.2021.3071142
Intelligent autonomous user discovery and link maintenance for mmWave and TeraHertz devices with directional antennas
|Author:||Khan, Zaheer1; Lehtomäki, Janne J.1; Selis, Valerio2;|
1Faculty of Information Technology and Electrical Engineering, University of Oulu, 90120 Oulu
2Department of Electrical and Electronics Engineering, University of Liverpool, Liverpool L69 3GJ, U.K.
3Department of Electronic Engineering, University of York, York YO10 5DD, U.K.
4Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, U.K.
|Online Access:||PDF Full Text (PDF, 2.6 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2022012610367
IEEE Communications Society,
|Publish Date:|| 2022-01-26
Use of smart directional antennas in handheld devices to generate a narrow beam in different directions for mmWave/TeraHertz communications present significant challenges. Devices using such antennas may have to scan several different directions in three-dimensional (3D) space to discover another user or an access point, a process that can result in problematic delays. Moreover, small movements of a user/device in the form of rotation and/or displacement may cause the discovered link to be lost. This paper proposes adaptive link discovery algorithms for devices in both infrastructure/ad hoc networks and evaluates their performance in terms of time-to-discovery. We show that one of the two proposed methods provides guaranteed discovery. We use an inertial measurement unit sensor to help intelligently rediscover a lost/degraded link. We propose sensor assisted link prediction methods for low-latency rediscovery in 3D space. We evaluate the effectiveness of our prediction-based rediscovery methods by testing them with real datasets representing various user/device 3D rotation patterns. We show that the smoothing based rediscovery can reach the prediction accuracy to 100% when two antenna sectors are searched, and it reduces the time-to-rediscovery by up to Sx (S times) as compared to the time-to-discovery, where S is the number of antenna sectors.
IEEE transactions on cognitive communications and networking
|Pages:||1200 - 1215|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
This work has received funding from Infotech Oulu, the EU Horizon 2020 (No 761794, TERRANOVA) and from the Academy of Finland 6Genesis Flagship (grant 318927).
|EU Grant Number:||
(761794) TERRANOVA - Terabit/s Wireless Connectivity by TeraHertz innovative technologies to deliver Optical Network Quality of Experience in Systems beyond 5G
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
© The Author(s) 2021. This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0.