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Conference Paper
Residual Attention Assisted Calibrated Beam Training for mmWave Communication Systems
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- Authors
- Jihyung Kim, Soyoung Yoo, Junghyun Kim
- Issue Date
- 2023-07
- Citation
- International Conference on Computer Communication and Networks (ICCCN) 2023, pp.1-2
- Language
- English
- Type
- Conference Paper
- Abstract
- We propose a novel framework named CNN-RALSTM model, which aims to enhance the accuracy of beam prediction in deep learning-based calibrated beam training for mmWave communications systems. Our approach differs from prior works as we leverage a residual attention network to extract features from complex signals efficiently during the training phase. The experimental results substantiate the effectiveness of our residual attention network and demonstrate that the proposed model yields better performance.
- KSP Keywords
- Communication system, Communications system, Complex Signal, Learning-based, Proposed model, deep learning(DL), extract features, mmWave communication, training phase