A TDMA protocol with reinforcement learning slot selection for MANETs. (8th May 2021)

• Record Type: Journal Article
• Authors: Lin, Chih-Yu; Wang, Chih-Hsiang; Tseng, Yu-Chee
• Is Part Of: International journal of ad hoc and ubiquitous computing. Volume 37:Number 1(2021)
• Page Start: 16
• Page End: 25
• Publication Date: 2021-05-08
• Subjects: medium access control -- MAC -- mobile ad hoc networks -- MANETs -- ns-3 -- reinforcement learning -- slot assignment -- time division multiple access -- TDMA; Ubiquitous computing -- Periodicals; Embedded computer systems -- Periodicals; Electronic data processing -- Distributed processing -- Periodicals; Wireless communication systems -- Periodicals; Computer architecture -- Periodicals; 004.2
• Languages: English
• ISSNs: 1743-8225

Abstract

With the rapid development of wireless communication and the advantage of infrastructure-less technologies, mobile ad hoc networks (MANETs) have attracted great attention on military and rescue applications. Medium access control is an important issue in MANETs. Contention-based MAC protocols (e.g., CSMA) do not ensure a reliable transmission due to the possibility of collisions. On the contrary, schedule-based MAC protocols (e.g., TDMA) can solve the collision problem with a scheduled transmission plan. However, under an infrastructure-less environment, it is non-trivial for each node to determine its own transmission plan. This work investigates how to use reinforcement learning (RL) to help nodes determine their transmission plans in a TDMA protocol. More precisely, we design a cross-layer TDMA protocol with a RL-based slot selection algorithm. We have validated the proposed protocol by the ns-3 network simulator.