Model-Driven Deep Learning for MIMO Detection

By Hengtao He, Chao-Kai Wen, Shi Jin, Geoffrey Y. Li. IEEE Transactions on Signal Processing, 2020

419 citations recorded by the source corpus.

In this paper, we investigate the model-driven deep learning (DL) for MIMO detection. In particular, the MIMO detector is specially designed by unfolding an iterative algorithm and adding some trainable parameters. Since the number of trainable parameters is much fewer than the data-driven DL based signal detector, the model-driven DL based MIMO detector can be rapidly trained with a much smaller data set. The proposed MIMO detector can be extended to soft-input soft-output detection easily. Furthermore, we investigate joint MIMO channel estimation and signal detection (JCESD), where the detector takes channel estimation error and channel statistics into consideration while channel estimation is refined by detected data and considers the detection error. Based on numerical results, the model-driven DL based MIMO detector significantly improves the performance of corresponding traditional iterative detector, outperforms other DL-based MIMO detectors and exhibits superior robustness to various mismatches.

Subfields: Artificial Intelligence, Molecular Biology, Plant Science

View Paper: https://www.semanticscholar.org/paper/0a614c46b2fababc0a9781501917e256922c99ba

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In Artificial Intelligence

1. Zhenzi Weng
2. Wuyang Chen
3. Zhangyang Wang
4. Tianlong Chen
5. Jialin Liu
6. Howard Heaton
7. Xiaohan Chen
8. Zhijin Qin

In Molecular Biology

1. Wuyang Chen
2. Zhenzi Weng
3. Tianlong Chen
4. Zhangyang Wang
5. Zhijin Qin
6. Wotao Yin

In Plant Science

1. Zhenzi Weng
2. Zhangyang Wang
3. Zhijin Qin

Citations in the corpus

• Learning to Optimize: A Primer and A Benchmark (2021, background): “resource management [195; 201; 56], channel estimation [80], signal detection [80] and LDPC coding [215].”
• Semantic Communication Systems for Speech Transmission (2021, methodology): “For example, the E2E learning systems have been employed in orthogonal frequency division multiplexing (OFDM) systems [15], [16], as well as in multiple-input multiple-output (MIMO) systems [17], [18].”