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Frontiersin SI on ML Wireless 2023 : SI on Machine Learning-Based Spectrum Occupancy Prediction and Resource Allocation/Management for Wireless Communication Systems | |||||||||||||
Link: https://www.frontiersin.org/research-topics/53759/ | |||||||||||||
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Call For Papers | |||||||||||||
If you are working on Cognitive Radio Spectrum Sensing and Resource
Allocation topics, you may be interested in contributing to the Special Issue (Research Topic) titled "Machine Learning-Based Spectrum Occupancy Prediction and Resource Allocation/Management for Wireless Communication Systems" in the Wireless Communications Section of the Journal Frontiers in Communications and Networks. https://www.frontiersin.org/research-topics/53759/ Topics of interest include (but are not limited to): 1. Designing novel ML models or algorithms for spectrum occupancy prediction and resource allocation/management. 2. Real-world experiments for spectrum occupancy prediction and resource allocation/management. 3. Theoretical comparison of ML models with model-based approaches 4. Novel feature selection methods for ML models in spectrum occupancy prediction and resource allocation/management problems 5. Complexity, accuracy, and memory requirements comparisons of ML algorithms for spectrum occupancy prediction and resource allocation/management 6. ML-based multi-dimensional spectrum occupancy prediction and resource allocation/management algorithms design and comparisons Important Dates: Abstract Submission Deadline 07 Sep 2023 Manuscript Submission Deadline 07 Jan 2024 Guest Editors: Mehmet Ali Aygul, Sanjay Dhar Roy, H. Birkan Yilmaz, Muhammad Amjad Frontiers was the 3rd most-cited publisher in 2021. ( https://www.frontiersin.org/about/impact ) Please note that publishing fees are applied to accepted articles, but the team at Frontiers is happy to inform and advise you in this regard. Authors and institutions with insufficient funding will be eligible for discounts to their Article Processing Charges. This includes authors in countries classified by the World Bank as low and low-middle income economies. |
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