Optimizing Energy and Spectrum in Cognitive IoT Networks

Background: The rapid growth of Internet of Things (IoT) applications is placing increasing pressure on limited spectrum resources and energy-constrained wireless devices. Cognitive IoT networks address these challenges by enabling intelligent spectrum sensing, dynamic spectrum access, adaptive transmission, and context-aware resource management. However, coordinating spectrum utilization and energy consumption remains difficult due to heterogeneous devices, uncertain channel conditions, interference, mobility, and diverse quality-of-service requirements. Emerging technologies such as machine learning, edge intelligence, energy harvesting, reconfigurable intelligent surfaces, and integrated sensing and communications offer new opportunities to improve network efficiency and sustainability. This Research Topic seeks original studies developing models, algorithms, protocols, and experimental solutions for jointly optimizing energy and spectrum resources across 5G-Advanced, 6G, industrial, smart-city, healthcare, transportation, and mission-critical applications.Goal: This Research Topic aims to advance intelligent methodologies for jointly optimizing energy efficiency and spectrum utilization in cognitive IoT networks. Despite progress in cognitive radio and IoT, many solutions address energy management and spectrum allocation independently, causing suboptimal performance, reduced scalability, and limited adaptability to dynamic environments. Emerging 5G-Advanced and 6G ecosystems demand autonomous, AI-driven, sustainable communication for massive heterogeneous IoT deployments.Contributions from academia and industry present theoretical, algorithmic, and experimental work integrating artificial intelligence, machine learning, edge intelligence, energy harvesting, wireless power transfer, integrated sensing and communications (ISAC), reconfigurable intelligent surfaces (RIS), and advanced resource management, spanning spectrum sensing and sharing, energy-aware protocols, cross-layer optimization, secure and resilient cognitive networking, and applications in smart cities, industrial IoT, healthcare, transportation, agriculture, and other mission-critical systems, fostering scalable, sustainable, intelligent cognitive IoT solutions that maximize spectrum efficiency, prolong network lifetime, and enhance the performance and reliability of next-generation wireless networks.Scope and information for authors: This Research Topic welcomes original research articles, review papers, perspective articles, brief research reports, and case studies addressing energy- and spectrum-efficient cognitive IoT networks. We invite contributions covering, but not limited to, cognitive radio and dynamic spectrum access, AI/ML-driven spectrum sensing and resource allocation, joint energy-spectrum optimization, energy harvesting and wireless power transfer, edge intelligence and federated learning, reconfigurable intelligent surfaces (RIS), integrated sensing and communications (ISAC/JSAC), cross-layer optimization, security and privacy, green and sustainable networking, 6G-enabled cognitive networks, and applications in smart cities, industrial IoT, healthcare, transportation, agriculture, and critical infrastructure. Theoretical advances, optimization frameworks, protocols, experimental testbeds, datasets, and real-world deployments are particularly encouraged. Manuscripts should emphasize originality, technical rigor, and practical relevance to next-generation intelligent wireless systems. Topic editors: Kelechi Hilary Anabi, Mohammed H. Alsharif, Augustine O. Nwajana Source: https://www.frontiersin.org/research-topics/84517/optimizing-energy-and-spectrum-in-cognitive-iot-networks