Mal-Net: multi-scale feature extraction and attention mechanism lightweight network for CSI feedback

Jinjie Song; Hongming Chen; Xiang Zhao; Chenyu Zhang; Yiting Wu; Qihong Ye

doi:10.1117/12.3006013

10 October 2023 Mal-Net: multi-scale feature extraction and attention mechanism lightweight network for CSI feedback

Jinjie Song, Hongming Chen, Xiang Zhao, Chenyu Zhang, Yiting Wu, Qihong Ye

Proceedings Volume 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023); 1279952 (2023) https://doi.org/10.1117/12.3006013
Event: 3rd International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 2023, Kuala Lumpur, Malaysia

Abstract

Massive multiple-input multiple-output (MIMO) system is one of the wireless technologies with great research significance based on channel state information (CSI). As the complexity of the CSI matrix increases, CSI feedback faces many challenges and limitations. This paper proposes a neural network composed of the encoder-decoder framework, which can effectively compress and recover CSI. The network utilizes a channel information generation module and multi-scale feature extraction module to enhance the information acquisition ability of the CSI matrix. At the same time, it reduces the computational complexity of the network by using lightweight architecture. Experimental results show that the network outperforms other advanced deep-learning methods at multiple compression rates.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinjie Song, Hongming Chen, Xiang Zhao, Chenyu Zhang, Yiting Wu, and Qihong Ye "Mal-Net: multi-scale feature extraction and attention mechanism lightweight network for CSI feedback", Proc. SPIE 12799, Third International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2023), 1279952 (10 October 2023); https://doi.org/10.1117/12.3006013

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KEYWORDS

Convolution

Matrices

Feature extraction

Multiple input multiple output

Network architectures

Deep learning

Design and modelling

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