Dear Colleagues,

During approximately the past twenty years, the paradigm of mobile communications has changed the modalities through which users relate to technology, considering both the comfort and functional aspects of their lives. The specification and implementation of new protocols and technologies designed for mobile scenarios, such as 5G, HetNets, UAVs, and autonomous vehicles, have significantly expanded the field of research in the scope of mobile technologies. Considering the 5G environments especially, certain deployed infrastructures, such as IoT-networked devices, determine an opportunity to thoroughly analyze several aspects of human life, fully considering the advantages of next-generation mobile networks pertaining to the environment, health, energy consumption, or mobile computing.

Next-generation mobile networks, such as the ones determined by technologies, e.g., 5G and beyond, define a field of study interesting for researchers, practitioners, and end users alike. Hence, there is an objective need to investigate how relevant technological patterns, e.g., artificial intelligence (AI) techniques such as deep learning and artificial neural networks (ANN), can be used in a dynamic fashion in order to approach the numerous challenges in the scope of the Internet of Things (IoT). As an example, machine learning is one of the most promising artificial intelligence (AI) tools, used, for example, in order to support the function of smart radio terminals. Moreover, next-generation mobile networks should be capable of using low-latency data transmission channels in order to reliably manage the Internet of Things (IoT) devices in real-time dynamic environments, requiring specialized network cores integrating advanced algorithmic patterns and technologies. These applications generate a large amount of data, which can be naturally assimilated to the category of big data, and should be collected, transmitted, and processed in a real-time or almost real-time fashion.

Additionally, there are intrinsic architectural problems requiring observation, such as, for example, the 5G backhaul infrastructure involving a greater degree of topological symmetry compared to previous-generation wireless standards, a problem also constituting an important part of this Special Issue’s scope.

Consequently, it is important to disseminate the relevant scientific contributions reporting ideas concerning the real-world usage of next-generation technologies such as 5G and 6G, also including related research topics. Therefore, the scope of this Special Issue is to collect contributions related to the aforementioned problems and concepts. Consequently, the possible research topics of interest include, but are certainly not limited to, the following:

• Integration of different and recent mobile communication technologies with 5G standards;
• Protocols and algorithms for environmental sensing suitable for 5G networks;
• Low-power wide-area network (LPWAN) technologies for wireless sensor networks and IoT;
• Studies regarding the architectural features of next-generation mobile networks discussing the topological symmetries and other particular structural aspects and their influence on the real-world behavior of the respective next-generation networks;
• Applications of mobile and/or wearable sensing for healthcare and other sensible use case scenarios based on 5G connectivity;
• Ultra-low latency and real-time applications in 5G networks;
• Vehicular protocols and their integration with other technologies (vehicular ad hoc networks—VANETs; 4G, 5G, mobile IP, etc.);
• Network planning and network slicing in the context of 5G networks;
• Applications and protocols related to sustainable computing in the context of 5G;
• Beyond 5G: 6G-enabling technologies, research challenges, open problems, potential solutions, and applications.

Dr. Razvan Bocu
Dr. Sabin Tabirca
Dr. Daniel C. Doolan
Guest Editors

Manuscript Submission Information

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• cognitive wireless sensor networks
• Internet of Things (IoT)
• artificial intelligence (AI)
• machine learning (ML)
• smart radio
• smart spectrum utilization
• network functions virtualization (NFV)
• 5G
• 6G
• mobile data privacy