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LEARNING-BASED SPECTRUM OCCUPANCY PREDICTION EXPLOITING MULTI-DIMENSIONAL CORRELATION

机译:基于学习的多维相关频谱占用率预测

摘要

The present disclosure relates to a spectrum occupancy prediction, which employs a first trainable module and a second trainable module. The first and the second trainable modules predict spectrum occupancy at a respective first and second communication devices based on past occupancies and/or occupancies in adjacent subband(s). The prediction from the first trainable module and the second trainable module is input to a trainable output (third) module, which then provides the spectrum occupancy prediction.
机译:本发明涉及一种频谱占用预测,其采用第一可训练模块和第二可训练模块。第一和第二可训练模块基于过去的占用和/或相邻子带中的占用预测各自的第一和第二通信设备处的频谱占用。来自第一可训练模块和第二可训练模块的预测被输入到可训练输出(第三)模块,该模块随后提供频谱占用预测。

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