Department Publications

Unmanned aerial vehicles (UAVs)-assisted communication systems are considered as a promising technology in diverse verticals. This paper studies the deployment of UAVs in wireless sensor network (WSN) systems. Considering the energy-constrained nature of the wireless sensors, we have proposed a multi-UAV deployment algorithm that minimizes the maximum power transmitted among the sensor nodes (SN) for given minimum data collection rate, minimum data-transferring rate, maximum power and height constraints. The problem is divided into three subproblems in order to reduce the complexity involved in solving them as a single problem. The subproblems are UAV-SN association, 2D positioning of the UAVs and the altitude optimization of the UAVs. Each subproblem is optimized by fixing other parameters as constant. First, the UAV-SN association is addressed using a customized Gale–Shapley …

It is envisioned that 6G networks will be supported by key architectural principles, including intelligence, decentralization, interoperability, and digitalization. With the advances in artificial intelligence (AI) and machine learning (ML), embedding intelligence into the foundation of wireless communication systems is recognized as essential for 6G and beyond. Existing radio access network (RAN) architectures struggle to meet the ever growing demands for flexibility, automation, and adaptability required to build self-evolving and autonomous wireless networks. In this context, this paper explores the transition towards AI-driven RAN (AI-RAN) by developing a novel AI-RAN framework whose performance is evaluated through a practical scenario focused on intelligent orchestration and resource optimization. Besides, the paper reviews the evolution of RAN architectures and sheds light on key enablers of AI-RAN including digital twins (DTs), intelligent reflecting surfaces (IRSs), large generative AI (GenAI) models, and blockchain (BC). Furthermore, it discusses the deployment challenges of AI-RAN, including technical and regulatory perspectives, and outlines future research directions incorporating technologies such as integrated sensing and communication (ISAC) and agentic AI.

The emergence of 5G technology has transformed network architecture, with network slicing technology standing out as a crucial feature for managing diverse and demanding applications. This innovative technology allows the creation of multiple virtual networks within a single physical infrastructure, each dedicated to specific needs such as latency, bandwidth, and reliability. These capabilities are vital for supporting services like enhanced mobile broadband, ultra-reliable low-latency communications, and massive machine-type communications. Predicting the optimal configuration of network slices is challenging due to the complex and dynamic nature of 5G environments. While traditional methods often lack the necessary accuracy, machine learning models have shown promise in addressing this challenge. However, the adoption of these models introduces the challenge of interpretability, as understanding how …

The rapid evolution of network technologies and frequent network intrusions have amplified the demand for intrusion detection systems (IDSs) powered by artificial intelligence (AI). However, the performance of IDSs is limited by labeled intrusion data and class imbalances in existing datasets. Collecting such data through live network simulations is costly, insecure, and poses regulatory challenges. This paper presents a multi-model framework that uses a conditional tabular generative adversarial network (CTGAN) to synthesize realistic network intrusion data. The framework addresses challenges such as unstable training, mode collapse, and handling mixed data types, which are common in most generative AI models when applied to non-Gaussian tabular data generation while validating the synthesized data through qualitative and quantitative analyses. Overlaid density histograms and cumulative distribution …

The energy consumption of telecommunication networks has been rising steadily due to the expansion of networks, power-hungry equipment and ever-increasing consumer demand. This contributes significantly to the world’s carbon footprint and greenhouse emissions. In particular, radio access networks (RANs) have been identified to have a larger contribution to the energy consumption of telecommunication networks, and a thorough evaluation is required to understand the avenues for energy reduction. In light of that, this study discusses various strategies to lower RAN power usage to minimize telecommunication’s environmental effect. Furthermore, a two-pronged strategy that combines dynamic operation management of base stations (BSs) and renewable energy integration is introduced to reduce the environmental impacts of RANs. With this hybrid strategy energy consumption and carbon footprint may be …

The demand for spectrum access continues to grow exponentially and dynamic spectrum access (DSA) is a candidate to alleviate issues with spectrum scarcity by adapting spectrum resources in real-time. Despite the benefits of intelligent DSA protocols, many algorithms are complex, and thus prohibitively difficult to implement in a real-time system. This paper proposes a contention-based access method named Guided-Aloha (or G-Aloha), that stems from the simple and well-known slotted-Aloha (S-Aloha) access method, for DSA in the context of primary users (PU) and secondary users (SU) of the network. The G-Aloha method is proposed for SU access to provide extended protection to the PU compared to the S-Aloha method by being guided by the knowledge from spectrum prediction (or spectrum forecasting), considering any potential regulatory requirements for protecting the PU. Using Markov modeling, an …

Virtual cycling is an engaging way to promote health and fitness while addressing the safety challenges of outdoor cycling. This paper introduces a Competitive Virtual Cycling (CVC) system that enhances user experience through immersive visuals, real-time competition, and low-latency networking. The system integrates virtual reality (VR) headsets, smart bicycle trainers, and real-world 360 ° videos to create a realistic gaming environment. A dynamic resistance feedback mechanism, driven by real-time sensor data from smart trainers and actuators, adjusts pedal resistance based on terrain variations, ensuring an authentic riding experience. To enhance engagement, we propose a novel avatar placement algorithm that optimizes competitor visibility in immersive, interactive races. Performance evaluations show that the system achieves a mean latency of 60 ms on a 4G network and 30 ms on a private 5G network …