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Titlebook: Cognitive Radio-Oriented Wireless Networks; 14th EAI Internation Adrian Kliks,Pawe? Kryszkiewicz,Micha? Sybis Conference proceedings 2019 I

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樓主: Jejunum
21#
發(fā)表于 2025-3-25 03:42:46 | 只看該作者
22#
發(fā)表于 2025-3-25 10:05:34 | 只看該作者
Martingale Inequalities and Related Toolser-provision its network considering the peak traffic. However, this inefficient approach results in a very high cost for the MNO. Alternatively, the MNO can expand its capacity with secondary spectrum discovered opportunistically whenever, wherever needed. While outsourcing the spectrum discovery t
23#
發(fā)表于 2025-3-25 13:45:14 | 只看該作者
24#
發(fā)表于 2025-3-25 18:09:07 | 只看該作者
Victor H. Pe?a,Tze Leung Lai,Qi-Man Shaomation and autonomous driving, the design of uRLLC of stringent requirements would be very challenging. Among novel solutions to satisfy uRLLC’s requirements, interface diversity is widely regarded as an efficient enabler of ultra-reliable connectivity. When mobile devices are connected to multiple
25#
發(fā)表于 2025-3-25 21:15:26 | 只看該作者
A General Framework for Self-Normalizationces. The main idea behind CR technology is to trigger secondary communications to utilize the unused spectral resources. However, CR technology heavily relies on spectrum sensing techniques which are applied to estimate the presence of primary user (PU) signals. This paper mostly focuses on novel an
26#
發(fā)表于 2025-3-26 03:35:33 | 只看該作者
27#
發(fā)表于 2025-3-26 06:36:48 | 只看該作者
Probability and Its Applicationsing has shown good performance in this task but using datasets not applicable to real world situations where topologies evolve over time. To remedy this, the work rests on a series of datasets gathered in the Future Internet of Things/Cognitive Radio Testbed?[.] to train a convolutional neural netwo
28#
發(fā)表于 2025-3-26 09:34:58 | 只看該作者
29#
發(fā)表于 2025-3-26 16:34:30 | 只看該作者
30#
發(fā)表于 2025-3-26 20:47:07 | 只看該作者
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