We argue for giving users the ability to lease bandwidth temporarily from any mobile network
operator. We propose, prototype, and evaluate a spectrum market for mobile network …

We consider a general online resource allocation model with bandit feedback and time-
varying demands. While online resource allocation has been well studied in the literature …

Bandits with arm selection constraints and bandits with switching costs have both gained
recent attention in wireless networking research. Pessimistic-optimistic algorithms, which …

The explosion in mobile data traffic together with the ever-increasing expectations for higher
quality of service call for the development of AI algorithms for wireless network optimization …

Bandit Convex Optimisation (BCO) is a powerful framework for sequential decision-making
in non-stationary and partially observable environments. In a BCO problem, a decision …

Wireless communication systems operate in complex time-varying environments. Therefore,
selecting the optimal configuration parameters in these systems is a challenging problem …

The design of personalized incentives or recommendations to improve user engagement is
gaining prominence as digital platform providers continually emerge. We propose a multi …

As large companies expand their operations, the importance of the business-to-business
(B2B) model is also on the rise. The network service selection problem serves as a typical …

The increasing complexity of modern mobile networks poses unprecedented challenges to
their optimization. Mobile Network Operators (MNOs) need to control a large number of …

In this study, we extended a contextual bandit algorithm, LinUCB, to facilitate cooperative
learning of an optimal strategy with intermittent information sharing. We then applied the …