Learning-based hybrid TDMA-CSMA MAC protocol for virtualized 802.11 WLANs

This paper presents an adaptive hybrid TDMA-CSMA MAC protocol to improve network performance and isolation among service providers (SPs) in a virtualized 802.11 network. Aiming to increase network efficiency, wireless virtual-ization provides the means to slice available resources among different SPs, with an urge to keep different slices isolated. Hybrid TDMA-CSMA can be a proper MAC candidate in such scenario benefiting from both the TDMA isolation power and the CSMA opportunistic nature. In this paper, we propose a dynamic MAC that schedules high-traffic users in the TDMA phase with variable size to be determined. Then, the rest of active users compete to access the channel through CSMA. The objective is to search for a scheduling that maximizes the expected sum throughput subject to SP reservations. In the absence of arrival traffic statistics, this scheduling is modeled as a multi-armed bandit (MAB) problem, in which each arm corresponds to a possible scheduling. Due to the dependency between the arms, existing policies are not directly applicable in this problem. Thus, we present an index-based policy where we update and decide based on learning indexes assigned to each user instead of each arm. To update the indexes, in addition to TDMA information, observations from CSMA phase are used, which adds a new exploration phase for the proposed MAB problem. Throughput and isolation performance of the proposed self-exploration-aided index-based policy (SIP) are evaluated by numerical results.