Related papers: Joint Optimisation of Load Balancing and Energy Ef…
The performance of cloud radio access network (C-RAN) is constrained by the limited fronthaul link capacity under future heavy data traffic. To tackle this problem, extensive efforts have been devoted to design efficient signal…
This paper considers a wireless powered multiuser mobile edge computing (MEC) system, where a multi-antenna access point (AP) employs the radio-frequency (RF) signal based wireless power transfer (WPT) to charge a number of distributed…
Integrating unmanned aerial vehicles (UAVs) into existing cellular networks encounters lots of challenges, among which one of the most striking concerns is how to achieve harmonious coexistence of aerial transceivers, inter alia, UAVs, and…
The Open Radio Access Network (O-RAN) architecture is reshaping the telecommunications landscape by enhancing network flexibility, openness, and intelligence. This paper establishes the requirements, evaluates the design tradeoffs, and…
As Open Radio Access Networks (O-RAN) continue to expand, AI-driven applications (xApps) are increasingly being deployed enhance network management. However, developing xApps without formal verification risks introducing logical…
We propose a new radio resource management algorithm which aims at minimizing the base station supply power consumption for multi-user MIMO-OFDM. Given a base station power model that establishes a relation between the RF transmit power and…
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…
Fifth-generation (5G) systems are increasingly studied as shared communication and computing infrastructure for connected vehicles, roadside edge platforms, and future unmanned-system applications. Yet results from simulators, host-OS…
The vision of AI-RAN convergence, as advocated by the AI-RAN Alliance, aims to unlock a unified 6G platform capable of seamlessly supporting AI and RAN workloads over shared infrastructure. However, the architectural framework and…
Reduction of wireless network energy consumption is becoming increasingly important to reduce environmental footprint and operational costs. A key concept to achieve it is the use of lean transmission techniques that dynamically…
The growing performance demands and higher deployment densities of next-generation wireless systems emphasize the importance of adopting strategies to manage the energy efficiency of mobile networks. In this demo, we showcase a framework…
The Open Radio Access Network (O-RAN), an industry-driven initiative, utilizes intelligent Radio Access Network (RAN) controllers and open interfaces to facilitate efficient spectrum sharing between LTE and NR RANs. In this paper, we…
This paper investigates the integration of Open Radio Access Network (O-RAN) within non-terrestrial networks (NTN), and optimizing the dynamic functional split between Centralized Units (CU) and Distributed Units (DU) for enhanced energy…
The emergence of the open radio access network (O-RAN) architecture offers a paradigm shift in cellular network management and service orchestration, leveraging data-driven, intent-based, autonomous, and intelligent solutions. Within O-RAN,…
In sixth-generation (6G) Open Radio Access Networks (O-RAN), proactive control is preferable. A key open challenge is delivering control-grade predictions within Near-Real-Time (Near-RT) latency and computational constraints under…
Large Language Models (LLMs) can revolutionize how we deploy and operate Open Radio Access Networks (O-RAN) by enhancing network analytics, anomaly detection, and code generation and significantly increasing the efficiency and reliability…
An orthogonal frequency division multiple access (OFDMA)-based primary user (PU) network is considered, which provides different spectral access/energy harvesting opportunities in RF-powered cognitive radio networks (CRNs). In this…
Mixture-of-Experts (MoE) models are typically pre-trained with explicit load-balancing constraints to ensure statistically balanced expert routing. Despite this, we observe that even well-trained MoE models exhibit significantly imbalanced…
Non-Orthogonal Multiple Access (NOMA) and Fog Radio Access Networks (FRAN) are promising candidates within the 5G and beyond systems. This work examines the benefit of adopting NOMA in an FRAN architecture with constrained capacity…
In this paper, energy efficient resource allocation is considered for an uplink hybrid system, where non-orthogonal multiple access (NOMA) is integrated into orthogonal multiple access (OMA). To ensure the quality of service for the users,…