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SPECTRAL SENSING AND ALLOCATION USING DEEP MACHINE LEARNING
SPECTRAL SENSING AND ALLOCATION USING DEEP MACHINE LEARNING
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机译:使用深度机器学习进行光谱感应和分配
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摘要
Methods and systems for identifying occupied areas of a radio frequency (RF) spectrum, identifying areas within that RF spectrum that are unusable for further transmissions, and identifying areas within that RF spectrum that are occupied but that may nonetheless be available for additional RF transmissions are provided. Implementation of the method then systems can include the use of multiple deep neural networks (DNNs), such as convolutional neural networks (CNN's), that are provided with inputs in the form of RF spectrograms. Embodiments of the present disclosure can be applied to cognitive radios or other configurable communication devices, including but not limited to multiple inputs multiple output (MIMO) devices and 5G communication system devices.
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