An Efficient Network with Novel Quantization Designed for Massive MIMO CSI Feedback
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arXiv
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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866914816611844096 |
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| author | Sun, Xinran Zhang, Zhengming Yang, Luxi |
| author_facet | Sun, Xinran Zhang, Zhengming Yang, Luxi |
| contents | The efficacy of massive multiple-input multiple-output (MIMO) techniques heavily relies on the accuracy of channel state information (CSI) in frequency division duplexing (FDD) systems. Many works focus on CSI compression and quantization methods to enhance CSI reconstruction accuracy with lower feedback overhead. In this letter, we propose CsiConformer, a novel CSI feedback network that combines convolutional operations and self-attention mechanisms to improve CSI feedback accuracy. Additionally, a new quantization module is developed to improve encoding efficiency. Experiment results show that CsiConformer outperforms previous state-of-the-art networks, achieving an average accuracy improvement of 17.67\% with lower computational overhead. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_20068 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | An Efficient Network with Novel Quantization Designed for Massive MIMO CSI Feedback Sun, Xinran Zhang, Zhengming Yang, Luxi Signal Processing The efficacy of massive multiple-input multiple-output (MIMO) techniques heavily relies on the accuracy of channel state information (CSI) in frequency division duplexing (FDD) systems. Many works focus on CSI compression and quantization methods to enhance CSI reconstruction accuracy with lower feedback overhead. In this letter, we propose CsiConformer, a novel CSI feedback network that combines convolutional operations and self-attention mechanisms to improve CSI feedback accuracy. Additionally, a new quantization module is developed to improve encoding efficiency. Experiment results show that CsiConformer outperforms previous state-of-the-art networks, achieving an average accuracy improvement of 17.67\% with lower computational overhead. |
| title | An Efficient Network with Novel Quantization Designed for Massive MIMO CSI Feedback |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2405.20068 |