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Autonomous Relay for Millimeter-Wave Wireless Communications
Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
Shanghai Key Laboratory of Scalable Computing and Systems at Shanghai Jiao Tong University, China..
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2017 (English)In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 35, no 9, 2127-2136 p.Article in journal (Refereed) Published
Abstract [en]

Millimeter-wave (mmWave) communication is the rising technology for next-generation wireless transmission. Benefited by its abundant bandwidth and short wavelength, mmWave is advanced in multi-gigabit transmittability and beamforming. In contrast, the short wavelength also makes mmWave easily blocked by obstacles. In order to bypass these obstacles, relays are widely needed in mmWave communications. Unmanned autonomous vehicles (UAVs), such as drones and self-driving robots, enable the mobile relays in real applications. Nevertheless, it is challenging for a UAV to find its optimal relay location automatically. On the one hand, it is difficult to find the location accurately due to the complex and dynamic wireless environment; on the other hand, most applications require the relay to forward data immediately, so the autonomous process should be fast. To tackle this challenge, we propose a novel method AutoRelay specialized for mmWave communications. In AutoRelay, the UAV samples the link qualities of mmWave beams while moving. Based on the real-time sampling, the UAV gradually adjusts its path to approach the optimal location by leveraging compressive sensing theory to estimate the link qualities in candidate space, which increases the accuracy and save the time. Performance results demonstrate that AutoRelay outperforms existing methods in achieving an accurate and efficient relay strategy.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2017. Vol. 35, no 9, 2127-2136 p.
National Category
Media and Communication Technology
Research subject
Mobile and Pervasive Computing
Identifiers
URN: urn:nbn:se:ltu:diva-64750DOI: 10.1109/JSAC.2017.2720518ISI: 000408055300015OAI: oai:DiVA.org:ltu-64750DiVA: diva2:1119145
Note

Validerad;2017;Nivå 2;2017-08-31 (rokbeg)

Available from: 2017-07-03 Created: 2017-07-03 Last updated: 2017-11-24Bibliographically approved

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Vasilakos, Athanasios V.
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