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As wireless communication systems become more advanced, Open Radio Access Networks (O-RAN) stand out as a notable framework that promotes interoperability and cost-effectiveness. An examination of the progression of RAN architectures, as…
Open Radio Access Networks (O-RAN) are emerging as a disruptive technology, revolutionising traditional mobile network architecture and deployments in the current 5G and the upcoming 6G era. Disaggregation of network architecture, inherent…
In this paper, we design a new smart softwaredefined radio access network (RAN) architecture with important properties like flexibility and traffic awareness for sixth generation (6G) wireless networks. In particular, we consider a…
The integration of Open Radio Access Network (O-RAN) principles into 5G networks introduces a paradigm shift in how radio resources are managed and optimized. O-RAN's open architecture enables the deployment of intelligent applications…
Deep Reinforcement Learning (DRL) has emerged as a powerful solution for meeting the growing demands for connectivity, reliability, low latency and operational efficiency in advanced networks. However, most research has focused on…
Open-Radio Access Network (O-RAN) has become an important paradigm for 5G and beyond radio access networks. This paper presents an xApp called xSlice for the Near-Real-Time (Near-RT) RAN Intelligent Controller (RIC) of 5G O-RANs. xSlice is…
5G and beyond cellular networks (NextG) will support the continuous execution of resource-expensive edge-assisted deep learning (DL) tasks. To this end, Radio Access Network (RAN) resources will need to be carefully "sliced" to satisfy…
The vision of 5G lies in providing high data rates, low latency (for the aim of near-real-time applications), significantly increased base station capacity, and near-perfect quality of service (QoS) for users, compared to LTE networks. In…
Open-radio access network (O-RAN) seeks to establish the principles of openness, programmability, automation, intelligence, and hardware-software disaggregation with interoperable and standard-compliant interfaces. It advocates for…
O-RAN (Open-Radio Access Network) offers a flexible, open architecture for next-generation wireless networks. Network slicing within O-RAN allows network operators to create customized virtual networks, each tailored to meet the specific…
Discretionary lane-change is one of the critical challenges for autonomous vehicle (AV) design due to its significant impact on traffic efficiency. Existing intelligent lane-change solutions have primarily focused on optimizing the…
Adversarial machine learning, focused on studying various attacks and defenses on machine learning (ML) models, is rapidly gaining importance as ML is increasingly being adopted for optimizing wireless systems such as Open Radio Access…
Connection management is an important problem for any wireless network to ensure smooth and well-balanced operation throughout. Traditional methods for connection management (specifically user-cell association) consider sub-optimal and…
Intent-based network automation is a promising tool to enable easier network management however certain challenges need to be effectively addressed. These are: 1) processing intents, i.e., identification of logic and necessary parameters to…
In this paper, we investigate a radio access network (RAN) slicing problem for Internet of vehicles (IoV) services with different quality of service (QoS) requirements, in which multiple logically-isolated slices are constructed on a common…
Vehicular communications integrated with the Radio Access Network (RAN) are envisioned as a breakthrough application for the 6th generation (6G) cellular systems. However, traditional RANs lack the flexibility to enable sophisticated…
Open Radio Access Networks (O-RAN) promise flexible 6G network access through disaggregated, software-driven components and open interfaces, but this programmability also increases operational complexity. Multiple control loops coexist…
In spite of the new opportunities brought about by the Open RAN, advances in ML-based network automation have been slow, mainly because of the unavailability of large-scale datasets and experimental testing infrastructure. This slows down…
Massive random access of devices in the emerging Open Radio Access Network (O-RAN) brings great challenge to the access control and management. Exploiting the bursting nature of the access requests, sparse active user detection (SAUD) is an…
Localization is increasingly becoming an integral component of wireless cellular networks. The advent of artificial intelligence (AI) and machine learning (ML) based localization algorithms presents potential for enhancing localization…