Related papers: Transformer-Based Wireless Traffic Prediction and …
Traffic optimization challenges, such as load balancing, flow scheduling, and improving packet delivery time, are difficult online decision-making problems in wide area networks (WAN). Complex heuristics are needed for instance to find…
The flexibility introduced with the Open Radio Access Network (O-RAN) architecture allows us to think beyond static configurations in all parts of the network. This paper addresses the issue related to predicting the power consumption of…
Network slicing envisions the 5th generation (5G) mobile network resource allocation to be based on different requirements for different services, such as Ultra-Reliable Low Latency Communication (URLLC) and Enhanced Mobile Broadband…
The explosive growth of global mobile traffic has lead to a rapid growth in the energy consumption in communication networks. In this paper, we focus on the energy-aware design of the network selection, subchannel, and power allocation in…
The rapid development of Wi-Fi technologies in recent years has caused a significant increase in the traffic usage. Hence, knowledge obtained from Wi-Fi network measurements can be helpful for a more efficient network management. In this…
In this paper, we examine the fundamental trade-off between radiated power and achieved throughput in wireless multi-carrier, multiple-input and multiple-output (MIMO) systems that vary with time in an unpredictable fashion (e.g. due to…
This paper deals with the improvement of energy efficiency in wireless sensor networks (WSN).Taking into consideration the power saving problem which is of crucial importance when the sensors are supplied by a limited power source, this…
Connected and autonomous vehicles (CAVs) possess the capability of perception and information broadcasting with other CAVs and connected intersections. Additionally, they exhibit computational abilities and can be controlled strategically,…
This work introduces an integrated approach to optimizing urban traffic by combining predictive modeling of vehicle flow, adaptive traffic signal control, and a modular integration architecture through distributed messaging. Using real-time…
Accurate network traffic prediction of base station cell is very vital for the expansion and reduction of wireless devices in base station cell. The burst and uncertainty of base station cell network traffic makes the network traffic…
Agentic artificial intelligence (AI) is emerging as a key enabler for autonomous radio access networks (RANs), where multiple large language model (LLM)-based agents reason and collaborate to achieve operator-defined intents. The open RAN…
Foundation models have shown great promise in various fields of study. A potential application of such models is in computer network traffic analysis, where these models can grasp the complexities of network traffic dynamics and adapt to…
In modern wireless network architectures, such as O-RAN, artificial intelligence (AI)-based applications are deployed at intelligent controllers to carry out functionalities like scheduling or power control. The AI "apps" are selected on…
The radio access network (RAN) accounts for the largest share of energy consumption in mobile networks, making it essential to understand how and where this energy is used, particularly as future networks move toward higher levels of…
The Open Radio Access Network (RAN) and its embodiment through the O-RAN Alliance specifications are poised to revolutionize the telecom ecosystem. O-RAN promotes virtualized RANs where disaggregated components are connected via open…
Connected Vehicles (CVs) can leverage the unique features of 5G and future 6G/NextG networks to enhance Intelligent Transportation System (ITS) services. However, even with advancements in cellular network generations, CV applications may…
Rate adaptation plays a key role in determining the performance of wireless LANs. In this paper, we introduce a semi-Markovian framework to analyze the performance of two of the most popular rate adaptation algorithms used in wireless LANs,…
In the rapidly evolving landscape of 5G and beyond, cloud-native Open Radio Access Networks (O-RAN) present a paradigm shift towards intelligent, flexible, and sustainable network operations. This study addresses the intricate challenge of…
Cellular traffic prediction is of great importance for operators to manage network resources and make decisions. Traffic is highly dynamic and influenced by many exogenous factors, which would lead to the degradation of traffic prediction…
The traffic assignment problem is essential for traffic flow analysis, traditionally solved using mathematical programs under the Equilibrium principle. These methods become computationally prohibitive for large-scale networks due to…