Related papers: Towards Optimal Adaptive Wireless Communications i…
Restless multi-armed bandits (RMAB) play a central role in modeling sequential decision making problems under an instantaneous activation constraint that at most B arms can be activated at any decision epoch. Each restless arm is endowed…
Multi-arm bandit (MAB) algorithms have been used to learn optimal beams for millimeter wave communication systems. Here, the complexity of learning the optimal beam linearly scales with the number of beams, leading to high latency when…
Motivated by wireless networks where interference or channel state estimates provide partial insight into throughput, we study a variant of the classical stochastic multi-armed bandit problem in which the learner has limited access to…
Effective budget allocation is crucial for optimizing the performance of digital advertising campaigns. However, the development of practical budget allocation algorithms remain limited, primarily due to the lack of public datasets and…
In time-varying wireless networks, the states of the communication channels are subject to random variations, and hence need to be estimated for efficient rate adaptation and scheduling. The estimation mechanism possesses inaccuracies that…
Wireless communication systems, such as wireless sensor networks and RFIDs, are increasingly adopted to transfer potential highly sensitive information. Since the wireless medium has a sharing nature, adversaries have a chance to eavesdrop…
We study broadcasting in multiple access channels with dynamic packet arrivals and jamming. Communication environments are represented by adversarial models that specify constraints on packet arrivals and jamming. We consider deterministic…
We study bandit best-arm identification with arbitrary and potentially adversarial rewards. A simple random uniform learner obtains the optimal rate of error in the adversarial scenario. However, this type of strategy is suboptimal when the…
In this paper, we consider the problem of wireless channel prediction, where we are interested in predicting the channel quality at unvisited locations in an area of interest, based on a small number of prior received power measurements…
Multi-agent systems often communicate over low-power shared wireless networks in unlicensed spectrum, prone to denial-of-service attacks. We consider the following scenario: multiple pairs of agents communicating strategically over shared…
IEEE 802.11ax uses the concept of primary and secondary channels, leading to the Dynamic Bandwidth Channel Access (DBCA) mechanism. By applying DBCA, a wireless station can select a wider channel bandwidth, such as 40/80/160 MHz, by…
We propose online algorithms for sequential learning in the contextual multi-armed bandit setting. Our approach is to partition the context space and then optimally combine all of the possible mappings between the partition regions and the…
We study a decentralized channel allocation problem in an ad-hoc Internet of Things network underlaying on the spectrum licensed to a primary cellular network. In the considered network, the impoverished channel sensing/probing capability…
In this paper, we look into the problem of channel assignment in multi-channel multi-radio wireless mesh networks. We propose a new learning automata based channel assignment scheme that adaptively improve network overall throughput by…
This paper proposes a novel policy for a group of agents to, individually as well as collectively, solve a multi armed bandit (MAB) problem. The policy relies solely on the information that an agent has obtained through sampling of the…
The restless bandit problem is one of the most well-studied generalizations of the celebrated stochastic multi-armed bandit problem in decision theory. In its ultimate generality, the restless bandit problem is known to be PSPACE-Hard to…
Due to the short and bursty incoming messages, channel access activities in a wireless random access system are often fractional. The lack of frequent data support consequently makes it difficult for the receiver to estimate and track the…
This work estimates the position and the transmit power of multiple co-channel wireless transmitters under model uncertainties. The model uncertainties include the number of the targets and the parameters of the path-loss model which enable…
This paper introduces the first asymptotically optimal strategy for a multi armed bandit (MAB) model under side constraints. The side constraints model situations in which bandit activations are limited by the availability of certain…
We study the problem of medium access control in domain of event-driven wireless sensor networks (WSNs). In this kind of WSN, sensor nodes send data to sink node only when an event occurs in the monitoring area. The nodes in this kind of…