Smart Communications for Cognitive Radio

Dear Colleagues,

Smart communications (SC) provide technological solutions based on adaptive capabilities that integrate signal processing, artificial intelligence (AI), networking, and communications techniques. SC generates a base on which paradigms such as Cognitive Radio (CR) and Cognitive Radio Networks (CRN) can evolve to deliver improvements in performance by integrating informed decisions, self-aware algorithms, and resource-aware adaptation, among others. Adaptation, reconfigurability, and learning are fundamental components that need to be united in order to generate new opportunities for CR and CRN to become strong future wireless communications technologies. Smart applications of CR will change how we shape complex environments with massive numbers of heterogeneous devices in many different contexts, such as in smart cities, smart energy, autonomous vehicles, intelligent transportation systems, Internet of Things (IoT), 5G and beyond 5G (B5G), to mention only a few. These massive numbers of devices will generate large amounts of information that need to be stored, secured, processed, and transmitted, and will produce complex scenarios with noise and interference that need to be treated to have reliable and successful communications. Design of detection and estimation techniques, as well as of learning methods, data management, error control, and data protection are of relevance for the CR paradigm, especially when those operate in a distributed manner.

This Special Issue will gather and disseminate cutting-edge research contributions to advance the development of smart communications for CR and CRN, including the design and analysis of efficient algorithms for CR and CRN. The topics of interest of this Special Issue include but are not limited to the following:

• Smart dynamic spectrum access, management, and usage;
• Cognitive learning for distributed multiuser communications environments;
• Smart co-existence and resource sharing for CRN;
• Reconfigurability for adaptation and learning of CR;
• Cognitive interference management techniques;
• Learning for channel estimation in CR;
• Smart localization algorithms in the context of CRN;
• CRN for cooperative and non-cooperative environments;
• Adaptive and distributed attack mitigation and detection in CRN;
• Connectivity analysis and evaluation of CRN infrastructure;
• Interoperability of CR and CRN with IoT, 5G, B5G.

Prof. Dr. Mort Naraghi-Pour
Dr. Cesar Vargas-Rosales
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• cognitive radio (CR)
• cognitive radio networks (CRN)
• channel estimation
• interference management
• spectrum access
• reconfigurable wireless networks
• distributed algorithms
• CR multiuser environments