Ehab Mahmoud Mohamed1, 2, *, Sherief Hashima3, 4, Kohei Hatano3, 5, Hani Kasban4, Mohamed Rihan6
CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 1987-2007, 2020, DOI:10.32604/cmc.2020.011816
Abstract The communication in the Millimeter-wave (mmWave) band, i.e., 30~300
GHz, is characterized by short-range transmissions and the use of antenna beamforming
(BF). Thus, multiple mmWave access points (APs) should be installed to fully cover a
target environment with gigabits per second (Gbps) connectivity. However, inter-beam
interference prevents maximizing the sum rates of the established concurrent links. In this
paper, a reinforcement learning (RL) approach is proposed for enabling mmWave
concurrent transmissions by finding out beam directions that maximize the long-term
average sum rates of the concurrent links. Specifically, the problem is formulated as a
multiplayer multiarmed bandit (MAB), where mmWave… More >
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