foadsohrabi / DL-ActiveLearning-BeamAlignment

Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment

Home Page:https://ieeexplore.ieee.org/abstract/document/9448070

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Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment

The codes provided here are corresponding to the numerical simulations in the paper entitled "Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment," which can be found on the following link: https://arxiv.org/abs/2012.13607

The codes are partitioned into two folders: 1- Detection: Considers the on-grid AoA detection. 2- Estimation: Considers the off-grid AoA estimation.

The titles of the subfolders inside these folders are self-explanatory. If you have any questions, feel free to reach me at: fsohrabi@ece.utoronto.ca

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Deep Active Learning Approach to Adaptive Beamforming for mmWave Initial Alignment

https://ieeexplore.ieee.org/abstract/document/9448070


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