mlsanityData to 7 Oct 2026

Attention Based Neural Networks for Wireless Channel Estimation

arXiv 2204.13465 ↗First posted 28 Apr 2022eess.SP cs.AIcited by 11

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Abstract (arXiv)

In this paper, we deploy the self-attention mechanism to achieve improved channel estimation for orthogonal frequency-division multiplexing waveforms in the downlink. Specifically, we propose a new hybrid encoder-decoder structure (called HA02) for the first time which exploits the attention mechanism to focus on the most important input information. In particular, we implement a transformer encoder block as the encoder to achieve the sparsity in the input features and a residual neural network as the decoder respectively, inspired by the success of the attention mechanism. Using 3GPP channel models, our simulations show superior estimation performance compared with other candidate neural network methods for channel estimation.

Key facts. Cited by 11 papers in the map (data through 7 Oct 2026). Builds on 13 of its 21 references that are in the map. First posted on arXiv 28 Apr 2022.

Builds on

13 of 21 references.

References · 13

  1. 2017Attention Is All You Needcited by 59,932
  2. 2016Layer Normalizationcited by 5,579
  3. 2016Gaussian Error Linear Units (GELUs)cited by 3,431
  4. 2017Non-local Neural Networkscited by 2,290
  5. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  6. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,218
  7. 2018Deep Learning-Based Channel Estimationcited by 75
  8. 2020Pruning the Pilots: Deep Learning-Based Pilot Design and Channel Estimation for MIMO-OFDM Systemscited by 18
  9. 2020Channel Estimation for Full-Duplex RIS-assisted HAPS Backhauling with Graph Attention Networkscited by 11
  10. 2021An Attention-Aided Deep Learning Framework for Massive MIMO Channel Estimationcited by 10
  11. 2022Low Complexity Channel estimation with Neural Network Solutionscited by 9
  12. 2021Deep Learning Based OFDM Channel Estimation Using Frequency-Time Division and Attention Mechanismcited by 4
1 more
  1. 2020OptComNet: Optimized Neural Networks for Low-Complexity Channel Estimationcited by 2

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 3; 2024: 0; 2025: 5; 2026: 2.

11 papers.

  1. 2023Channelformer: Attention based Neural Solution for Wireless Channel Estimation and Effective Online Trainingcited by 14
  2. 2023Achieving Robust Generalization for Wireless Channel Estimation Neural Networks by Designed Training Datacited by 4
  3. 2025Robust Channel Estimation for Optical Wireless Communications Using Neural Networkcited by 2
  4. 2023Joint Channel Estimation and Feedback with Masked Token Transformers in Massive MIMO Systemscited by 1
  5. 2025Transformer-Driven Neural Beamforming with Imperfect CSI in Urban Macro Wireless Channelscited by 1
  6. 2025AdaFortiTran: An Adaptive Transformer Model for Robust OFDM Channel Estimationcited by 1
  7. 2025Achieving Robust Channel Estimation Neural Networks by Designed Training Datacited by 1
  8. 2025ReQuestNet: A Foundational Learning model for Channel Estimationcited by 1
  9. 2022Learn to Adapt to New Environment from Past Experience and Few Pilotcited by 0
  10. 2026Hybrid Mamba-Attention Neural Architecture for Channel Estimationcited by 0
  11. 2026Brownian Bridge Diffusion-Based Joint Channel Estimation and Data Detection for Jamming-Resilient Receiverscited by 0