贝叶斯主动学习实现样本高效的 5G 无线电地图重构

IF 8.9 1区 计算机科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Transactions on Wireless Communications Pub Date : 2024-10-24 DOI:10.1109/twc.2024.3483112
Konstantinos D. Polyzos, Alireza Sadeghi, Wei Ye, Steven Sleder, Kodjo Houssou, Jeff Calder, Zhi-Li Zhang, Georgios B. Giannakis
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Bayesian Active Learning for Sample Efficient 5G Radio Map Reconstruction
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来源期刊
CiteScore
18.60
自引率
10.60%
发文量
708
审稿时长
5.6 months
期刊介绍: The IEEE Transactions on Wireless Communications is a prestigious publication that showcases cutting-edge advancements in wireless communications. It welcomes both theoretical and practical contributions in various areas. The scope of the Transactions encompasses a wide range of topics, including modulation and coding, detection and estimation, propagation and channel characterization, and diversity techniques. The journal also emphasizes the physical and link layer communication aspects of network architectures and protocols. The journal is open to papers on specific topics or non-traditional topics related to specific application areas. This includes simulation tools and methodologies, orthogonal frequency division multiplexing, MIMO systems, and wireless over optical technologies. Overall, the IEEE Transactions on Wireless Communications serves as a platform for high-quality manuscripts that push the boundaries of wireless communications and contribute to advancements in the field.
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