Data Analytics and Optimization for Hybrid Communication Systems
A special issue of Algorithms (ISSN 1999-4893).
Deadline for manuscript submissions: closed (15 September 2016) | Viewed by 4834
Special Issue Editor
2. Communications Engineering, University of the Basque Country (UPV/EHU), 48013 Bilbao, Bizkaia, Spain
Interests: machine learning; deep learning; meta-heuristic optimization; explainable artificial intelligence; responsible artificial intelligence; stream learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The last decade has experienced an upsurge of contributions aimed at validating the applicability of novel supervised learning models, clustering schemes and optimization algorithms to problems arising from a wide variety of fields. One such application scenario gravitates on the different paradigms that stem from the optimized management and operation of next-generation communication systems, especially in what regards the deployment of hybrid WAN/LAN/BAN wired/wireless networks, the incorporation of highly-directive transmission technologies, such as mmWave communications, the exploitation of massively captured information by such networks (coming either from its own operational processes or from the users of the network itself) and the consideration of energy efficiency in the allocation of radio resources. In all such paradigms, the use of novel optimization approaches (including the latest advances in swarm intelligence and bioinspired computation) and predictive modeling are called to play a crucial role to cope with the intrinsic challenges of an optimized, adaptive and efficient management and operation of such hybrid networks.
This rationale motivates the launch of a Special Issue of Algorithms is devoted to technical contributions in the wide fields of data analytics (clustering, predictive modeling) and optimization (with a focus on bioinspired solvers), applied to the management and optimization of hybrid communication systems. Specific applications of interest include, but are not limited to:
- Hybrid wireless/wired networking
- mmWave/uWave communications
- Body Area Networks
- Multiple user communications, including interference avoidance/alignment
- Synchronization methods
- Radio resource management (e.g., spectrum, power)
- Channel estimation and equalization
- Source/channel coding/decoding
- Data-based routing protocols
- Energy-efficient network topologies
- Dynamic resource allocation
- Data fusion techniques
- Cross-layer synergies among physical and upper (e.g., network) layers
- Implementation issues
- Survivability and reliability
- Network deployment
- Quality of Service / Quality of Experience
- Congestion control
Prof. Dr. Javier Del Ser Lorente
Guest Editor
Manuscript Submission Information
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Keywords
- Hybrid communication networks
- Resource allocation
- Bioinspired optimization and data analytics
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