Cognitive Radio Networks and Spectrum Sensing

Últimos artículos

• Faithful, Not Corrective: Message-Format Effects in Multi-Hop Agent Relays Are Tier-Dependent

  Zayx Shawn · 14 de julio de 2026

  When LLM agents hand off information to one another, does the message format matter? Two literatures disagree: format-optimization work reports that structured messages cut cost without hurting accuracy, while format-restriction work finds that imposing structure degrades generation -- and neither m…

• When Critics Disagree: Adaptive Reward Poisoning Attacks in RIS-Aided Wireless Control System

  Deemah H. Tashman, Soumaya Cherkaoui · 20 de mayo de 2026

  Reward-poisoning attacks present a significant risk to learning-based wireless control systems. Given this, we propose a Disagreement-Guided Reward Poisoning (DGRP) adaptive attack on a Soft Actor-Critic (SAC) agent. In a Cognitive Radio Network (CRN) environment assisted by Reconfigurable Intellige…

• Towards Intelligent Spectrum Management: Spectrum Demand Estimation Using Graph Neural Networks

  Mohamad Alkadamani, Amir Ghasemi, Halim Yanikomeroglu · 12 de marzo de 2026

  The growing demand for wireless connectivity, combined with limited spectrum resources, calls for more efficient spectrum management. Spectrum sharing is a promising approach; however, regulators need accurate methods to characterize demand dynamics and guide allocation decisions. This paper builds …

• Towards Flexible Spectrum Access: Data-Driven Insights into Spectrum Demand

  Mohamad Alkadamani, Amir Ghasemi, Halim Yanikomeroglu · 11 de marzo de 2026

  In the diverse landscape of 6G networks, where wireless connectivity demands surge and spectrum resources remain limited, flexible spectrum access becomes paramount. The success of crafting such schemes hinges on our ability to accurately characterize spectrum demand patterns across space and time. …

• AI-Enabled Data-driven Intelligence for Spectrum Demand Estimation

  Colin Brown, Mohamad Alkadamani, Halim Yanikomeroglu · 11 de marzo de 2026

  Accurately forecasting spectrum demand is a key component for efficient spectrum resource allocation and management. With the rapid growth in demand for wireless services, mobile network operators and regulators face increasing challenges in ensuring adequate spectrum availability. This paper presen…

• A Graph-Based Approach to Spectrum Demand Prediction Using Hierarchical Attention Networks

  Mohamad Alkadamani, Halim Yanikomeroglu, Amir Ghasemi · 11 de marzo de 2026

  The surge in wireless connectivity demand, coupled with the finite nature of spectrum resources, compels the development of efficient spectrum management approaches. Spectrum sharing presents a promising avenue, although it demands precise characterization of spectrum demand for informed policy-maki…

• Transformer-Based Cognitive Radio: Adaptive Modulation Strategies Using Transformer Models

  Andrea Melis, Andrea Piroddi, Roberto Girau · 16 de enero de 2026

  Cognitive Radio (CR) systems, which dynamically adapt to changing spectrum environments, could benefit significantly from advancements in machine learning technologies. These systems can be enhanced in terms of spectral efficiency, robustness, and security through innovative approaches such as the u…