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This paper introduces the novel concept of proactive resource allocation through which the predictability of user behavior is exploited to balance the wireless traffic over time, and hence, significantly reduce the bandwidth required to…
Life-cycle management of large-scale transportation systems requires determining a sequence of inspection and maintenance decisions to minimize long-term risks and costs while dealing with multiple uncertainties and constraints that lie in…
Artificial intelligence (AI) and Machine Learning (ML) are considered as key enablers for realizing the full potential of fifth-generation (5G) and beyond mobile networks, particularly in the context of resource management and…
In large-scale resource-constrained wireless networks, such as those prevalent in the Internet of Things (IoT), efficient communication scheduling remains a critical challenge. Among the various approaches, Time Division Multiple Access…
Diffusion models are vastly used in generative AI, leveraging their capability to capture complex data distributions. However, their potential remains largely unexplored in the field of resource allocation in wireless networks. This paper…
This work considers the orthogonal frequency division multiple access (OFDMA) technology that enables multiple unmanned aerial vehicles (multi-UAV) communication systems to provide on-demand services. The main aim of this work is to derive…
This paper proposes a multi-agent reinforcement learning based medium access framework for wireless networks. The access problem is formulated as a Markov Decision Process (MDP), and solved using reinforcement learning with every network…
The fast development of Artificial Intelligence (AI) agents provides a promising way for the realization of intelligent and customized wireless networks. In this paper, we propose a Wireless Multi-Agent System (WMAS), which can provide…
In this paper, resource allocation for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) downlink networks with large numbers of base station antennas is studied. Assuming perfect channel state…
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…
The fundamental design of wireless systems toward AI-native 6G and beyond is driven by the need for ever-increasing demand of mobile data traffic, extreme spectral efficiency, and adaptability across diverse service scenarios. To overcome…
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…
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…
With the rapid development of future wireless communication, the combination of NOMA technology and millimeter-wave(mmWave) technology has become a research hotspot. The application of NOMA in mmWave heterogeneous networks can meet the…
This letter introduces a novel framework to optimize the power allocation for users in a Rate Splitting Multiple Access (RSMA) network. In the network, messages intended for users are split into different parts that are a single common part…
The recent success of large language models (LLMs) has spurred their application in various fields. In particular, there have been efforts to integrate LLMs into various aspects of wireless communication systems. The use of LLMs in wireless…
Adaptive Radio Resource Allocation is essential for guaranteeing high bandwidth and power utilization as well as satisfying heterogeneous Quality-of-Service requests regarding next generation broadband multicarrier wireless access networks…
Device-to-device (D2D) technology is one of the key research areas in 5G/6G networks, and full-duplex (FD) D2D will further enhance its spectral efficiency (SE). In recent years, deep learning approaches have shown remarkable performance in…
Federated learning (FL) has found many successes in wireless networks; however, the implementation of FL has been hindered by the energy limitation of mobile devices (MDs) and the availability of training data at MDs. How to integrate…
Subscriber satisfaction and maximum radio resource utilization are the pivotal criteria in communication system design. In multi-Carrier CDMA system, different paging algorithms are used for locating user within the shortest possible time…