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Simultaneously information and power transfer in mobile relay networks have recently emerged, where the relay can harvest the radio frequency (RF) energy and then use this energy for data forwarding and system operation. Most of the…

Device-to-device (D2D) technology enables direct communication between adjacent devices within cellular networks. Due to its high data rate, low latency, and performance improvement in spectrum and energy efficiency, it has been widely…

The deployment of small cell networks is seen as a major feature of the next generation of wireless networks. In this paper, a novel approach for cell association in small cell networks is proposed. The proposed approach exploits new types…

In recent years, with the explosive growth of data traffic, communication base stations (BSs) need to serve more and more users. Offloading traffic from BSs has become an efficient way to reduce the burden on BSs. Device-to-Device (D2D)…

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…

This work addresses resource allocation challenges in multi-cell wireless systems catering to enhanced Mobile Broadband (eMBB) and Ultra-Reliable Low Latency Communications (URLLC) users. We present a distributed learning framework tailored…

In this paper, a deep learning (DL) framework for the optimization of the resource allocation in multi-channel cellular systems with device-to-device (D2D) communication is proposed. Thereby, the channel assignment and discrete transmit…

Locally caching contents at the network edge constitutes one of the most disruptive approaches in $5$G wireless networks. Reaping the benefits of edge caching hinges on solving a myriad of challenges such as how, what and when to…

Interference-aware resource allocation of time slots and frequency channels in single-antenna, halfduplex radio wireless sensor networks (WSN) is challenging. Devising distributed algorithms for such task further complicates the problem.…

Scarcity of health care resources could result in the unavoidable consequence of rationing. For example, ventilators are often limited in supply, especially during public health emergencies or in resource-constrained health care settings,…

In this paper, we study the problem of Quality of Experience (QoE) aware resource allocation in wireless systems. In particular, we consider application-aware joint Bandwidth-Power allocation for a small cell. We optimize a QoE metric for…

Distributed edge learning (DL) is considered a cornerstone of intelligence enablers, since it allows for collaborative training without the necessity for local clients to share raw data with other parties, thereby preserving privacy and…

This paper considers a multi-user simultaneous wireless information and power transfer (SWIPT) system with a non-linear energy harvesting model, in which a multi-antenna base station (BS) estimates the downlink channel state information…

In this work, we consider the radio resource allocation problem in a wireless system with various integrated functionalities, such as communication, sensing and computing. We design suitable resource management techniques that can…

We consider a Wireless Networked Control System (WNCS) where sensors provide observations to build a DT model of the underlying system dynamics. The focus is on control, scheduling, and resource allocation for sensory observation to ensure…

By deploying machine-learning algorithms at the network edge, edge learning can leverage the enormous real-time data generated by billions of mobile devices to train AI models, which enable intelligent mobile applications. In this emerging…

There is an increasing interest in a fast-growing machine learning technique called Federated Learning, in which the model training is distributed over mobile user equipments (UEs), exploiting UEs' local computation and training data.…

Emerging wireless AR/VR applications require real-time transmission of correlated high-fidelity speech from multiple resource-constrained devices over unreliable, bandwidth-limited channels. Existing autoencoder-based speech source coding…

We consider a radio resource management (RRM) problem in a multi-user wireless network, where the goal is to optimize a network-wide utility function subject to constraints on the ergodic average performance of users. We propose a…

Driven by mission-critical applications in modern industrial systems, the 5th generation (5G) communication system is expected to provide ultra-reliable low-latency communications (URLLC) services to meet the quality of service (QoS)…