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arXiv · 2108.03297

Joint AP Probing and Scheduling: A Contextual Bandit Approach

Tianyi Xu·Ding Zhang·Parth H. Pathak·Zizhan Zheng
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Abstract

We consider a set of APs with unknown data rates that cooperatively serve a mobile client. The data rate of each link is i.i.d. sampled from a distribution that is unknown a priori. In contrast to traditional link scheduling problems under uncertainty, we assume that in each time step, the device can probe a subset of links before deciding which one to use. We model this problem as a contextual bandit problem with probing (CBwP) and present an efficient algorithm. We further establish the regret of our algorithm for links with Bernoulli data rates. Our CBwP model is a novel extension of the classic contextual bandit model and can potentially be applied to a large class of sequential decision-making problems that involve joint probing and play under uncertainty.

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Tianyi Xu, Ding Zhang, Parth H. Pathak, Zizhan Zheng. 2021-08-06. Joint AP Probing and Scheduling: A Contextual Bandit Approach. https://doi.org/10.1109/milcom52596.2021.9652990

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