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The ever-increasing demand for broadband and IoT wireless connectivity has recently urged the regulators around the world to start opening the 6 GHz spectrum for unlicensed use. These bands will, for example, permit the use of additional…

Emerging wireless services with extremely high data rate requirements, such as real-time extended reality applications, mandate novel solutions to further increase the capacity of future wireless networks. In this regard, leveraging large…

Most reinforcement learning (RL) recommendation systems designed for edge computing must either synchronize during recommendation selection or depend on an unprincipled patchwork collection of algorithms. In this work, we build on…

We study the interaction of WiFi and 5G cellular networks as they exploit the recently unlocked 6-GHz spectrum for unlicensed access while conforming to the constraints imposed by the incumbent users. We derive the theoretical performance…

As two major players in terrestrial wireless communications, Wi-Fi systems and cellular networks have different origins and have largely evolved separately. Motivated by the exponentially increasing wireless data demand, cellular networks…

Reinforcement Learning is gaining attention by the wireless networking community due to its potential to learn good-performing configurations only from the observed results. In this work we propose a stateless variation of Q-learning, which…

Autonomous mapping of unknown environments is a critical challenge, particularly in scenarios where time is limited. Multi-agent systems can enhance efficiency through collaboration, but the scalability of motion-planning algorithms remains…

Listen-Before-Talk (LBT) has been adopted as the spectrum sharing technique that guarantees a fair LTE/Wi-Fi coexistence in the unlicensed spectrum at the 5 GHz band. Differently, at mmWave bands, where beamforming is a must to overcome…

Future wireless networks require high throughput and energy efficiency. This paper studies using Reinforcement Learning (RL) to do transmission rate and power control for maximizing a joint reward function consisting of both throughput and…

Balancing exploration and exploitation is a fundamental part of reinforcement learning, yet most state-of-the-art algorithms use a naive exploration protocol like $\epsilon$-greedy. This contributes to the problem of high sample complexity,…

In this work, we consider the problem of network parameter optimization for rate maximization. We frame this as a joint optimization problem of power control, beam forming, and interference cancellation. We consider the setting where…

In this article, we introduce a game-theoretic learning framework for the multi-agent wireless network. By combining learning in artificial intelligence (AI) with game theory, several promising properties emerge such as obtaining high…

In the Bayesian Reinforcement Learning (BRL) setting, agents try to maximise the collected rewards while interacting with their environment while using some prior knowledge that is accessed beforehand. Many BRL algorithms have already been…

License Assisted Access (LAA) LTE (LTE-LAA) is a new type of LTE that aggregates the licensed LTE bands with the unlicensed bands via carrier aggregation. To operate in unlicensed bands, LTE-LAA adopts the listen-before-talk policy and…

In this work, we first describe a framework for the application of Reinforcement Learning (RL) control to a radar system that operates in a congested spectral setting. We then compare the utility of several RL algorithms through a…

Reinforcement learning (RL) problems are often phrased in terms of Markov decision processes (MDPs). In this thesis we go beyond MDPs and consider RL in environments that are non-Markovian, non-ergodic and only partially observable. Our…

LTE in the unlicensed band (LTE-U) is a promising solution to overcome the scarcity of the wireless spectrum. However, to reap the benefits of LTE-U, it is essential to maintain its effective coexistence with WiFi systems. Such a…

In this paper we address the issue of association fairness when Wi-Fi and LTE unlicensed (LTE-U) coexist on the same channel in the unlicensed 5 GHz band. Since beacon transmission is the first step in starting the association process in…

Motivated by the recent efforts in extending LTE to the unlicensed spectrum, we propose a novel spectrum sharing framework for the coopetition (i.e., cooperation and competition) between LTE and Wi-Fi in the unlicensed band. Basically, the…

The deployment of reconfigurable intelligent surfaces (RISs) introduces new challenges for resource allocation in multi-cell wireless networks, particularly when user loads are uneven across base stations. In this work, we consider RISs as…