2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC) 2017
DOI: 10.1109/pimrc.2017.8292296
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Adaptive learning based directional MAC protocol for millimeter wave (mmWave) wireless networks

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Cited by 6 publications
(2 citation statements)
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“…The neighbor discovery mechanism is a great choice for directional propagation systems, as it leads to the establishment of connections without redundancy transmission in random directions. Accordingly, a reinforcement learning (RL) based MAC protocol called adaptive learning directional medium access control (ALD-MAC) [ 70 ] was proposed to enable implicit cooperation between different nodes in the mmWave communication systems by combining a neighbor discovery algorithm with RL. In ALD-MAC, the channel access period is divided into a set of fixed-length frames.…”
Section: Distributed Protocolsmentioning
confidence: 99%
“…The neighbor discovery mechanism is a great choice for directional propagation systems, as it leads to the establishment of connections without redundancy transmission in random directions. Accordingly, a reinforcement learning (RL) based MAC protocol called adaptive learning directional medium access control (ALD-MAC) [ 70 ] was proposed to enable implicit cooperation between different nodes in the mmWave communication systems by combining a neighbor discovery algorithm with RL. In ALD-MAC, the channel access period is divided into a set of fixed-length frames.…”
Section: Distributed Protocolsmentioning
confidence: 99%
“…Given the wireless dynamic nature, it is unfeasible to design heuristics to cope with the network behavior beforehand. Because of that, some proposals [17] [152]- [158] are making use of ML algorithms to improve their MAC selection/configuration mechanisms. FullMAC implementations have been switched based on classifications learned from the environment.…”
Section: A Intelligent Mac Layer Adaptationmentioning
confidence: 99%