Related papers: A Model-Data Dual-Driven Resource Allocation Schem…
Optical wireless communication (OWC) systems are a promising communication technology that can provide high data rates into the tens of Tb/s and can support multiple users at the same time. This paper investigates the optimum allocation of…
Renewable energy resources (RERs) have been increasingly integrated into large-scale distributed power systems. Considering uncertainties and voltage fluctuation issues introduced by RERs, in this paper, we propose a deep reinforcement…
Federated learning (FL) has received significant attention in recent years for its advantages in efficient training of machine learning models across distributed clients without disclosing user-sensitive data. Specifically, in federated…
As the next-generation wireless communication system, Sixth-Generation (6G) technologies are emerging, enabling various mobile edge networks that can revolutionize wireless communication and connectivity. By integrating Generative…
5G and beyond wireless networks are the upcoming evolution for the current cellular networks to provide the essential requirement of future demands such as high data rate, low energy consumption, and low latency to provide seamless…
This paper presents an optimal network topology control framework using cutting-plane methods for efficient network partitioning with controllable edges. The objective is to enable real-time reconfiguration of interconnected sub-networks…
To support the newly introduced multimedia services with ultra-low latency and extensive computation requirements, resource-constrained end user devices should utilize the ubiquitous computing resources available at network edge for…
Next generation wireless networks face the challenge of increasing energy consumption while satisfying the unprecedented increase in the data rate demand. To address this problem, we propose a utility-based energy-efficient resource…
This paper addresses how to handle slice resources for 6G networks at different time scales in an architecture based on an open radio access network (ORAN). The proposed solution includes artificial intelligence (AI) at the edge of the…
The introduction of device-to-device (D2D) into cellular networks poses many new challenges in the resource allocation design due to the co-channel interference caused by spectrum reuse and limited battery life of user equipments (UEs). In…
We propose a novel approach to optimize fleet management by combining multi-agent reinforcement learning with graph neural network. To provide ride-hailing service, one needs to optimize dynamic resources and demands over spatial domain.…
We consider the broad class of decentralized optimal resource allocation problems in wireless networks, which can be formulated as a constrained statistical learning problems with a localized information structure. We develop the use of…
In wireless communications, transforming network into graphs and processing them using deep learning models, such as Graph Neural Networks (GNNs), is one of the mainstream network optimization approaches. While effective, the generative AI…
This study investigates wireless information and energy transfer for dual-hop amplify-and-forward full-duplex relaying systems. By forming energy efficiency (EE) maximization problem into a concave fractional program of transmission power,…
The increasing demand for electricity, coupled with the rise in greenhouse gas emissions, necessitates the integration of Renewable Energy Sources (RESs) into power grids. However, the fluctuating nature of RESs introduces new challenges in…
Device-to-device (D2D) communication is an effective technology enhancing spectral efficiency and network throughput of contemporary cellular networks. Typically, the users exploiting D2D reuse the same radio resources as common cellular…
Network modeling is a key enabler to achieve efficient network operation in future self-driving Software-Defined Networks. However, we still lack functional network models able to produce accurate predictions of Key Performance Indicators…
Machine-to-Machine (M2M) communication is crucial in developing Internet of Things (IoT). As it is well known that cellular networks have been considered as the primary infrastructure for M2M communications, there are several key issues to…
Multi-access edge computing (MEC) is seen as a vital component of forthcoming 6G wireless networks, aiming to support emerging applications that demand high service reliability and low latency. However, ensuring the ultra-reliable and…
As wireless connectivity continues to evolve towards 6G, there is an ever-increasing demand to not only deliver higher throughput, lower latency, and improved reliability, but also do so as efficiently as possible. To this point, the term…