Ultra-Reliable Communication in 5G mmWave Networks: A Risk-Sensitive Approach

In this letter, we investigate the problem of providing gigabit wireless access with reliable communication in 5G millimeter-wave (mmWave) massive multiple-input multiple-output networks. In contrast to the classical network design based on average metrics, we propose a distributed risk-sensitive re...

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Bibliographic Details
Published in:IEEE communications letters 2018-04, Vol.22 (4), p.708-711
Main Authors: Trung Kien Vu, Bennis, Mehdi, Debbah, Merouane, Latva-aho, Matti, Choong Seon Hong
Format: Article
Language:English
Subjects:
5G mobile communication
Array signal processing
Computer Science
Information Theory
MIMO communication
mmWave communication
Probability distribution
risk-sensitive learning
Transmitters
Ultra-reliable communication
Wireless communication
Wireless sensor networks
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Summary:In this letter, we investigate the problem of providing gigabit wireless access with reliable communication in 5G millimeter-wave (mmWave) massive multiple-input multiple-output networks. In contrast to the classical network design based on average metrics, we propose a distributed risk-sensitive reinforcement learning-based framework to jointly optimize the beamwidth and transmit power, while taking into account the sensitivity of mmWave links due to blockage. Numerical results show that our proposed algorithm achieves more than 9 Gbps of user throughput with a guaranteed probability of 90%, whereas the baselines guarantee less than 7.5 Gbps. More importantly, there exists a rate-reliability-network density tradeoff, in which as the user density increases from 16 to 96 per km 2 , the fraction of users that achieves 4 Gbps is reduced by 11.61% and 39.11% in the proposed and the baseline models, respectively.
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2018.2802902