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Deep Unfolding for Communications Systems: A Survey and Some New Directions

arXiv 1906.05774 ↗First posted 13 Jun 2019eess.SP cs.IT math.ITcited by 48

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Abstract (arXiv)

Deep unfolding is a method of growing popularity that fuses iterative optimization algorithms with tools from neural networks to efficiently solve a range of tasks in machine learning, signal and image processing, and communication systems. This survey summarizes the principle of deep unfolding and discusses its recent use for communication systems with focus on detection and precoding in multi-antenna (MIMO) wireless systems and belief propagation decoding of error-correcting codes. To showcase the efficacy and generality of deep unfolding, we describe a range of other tasks relevant to communication systems that can be solved using this emerging paradigm. We conclude the survey by outlining a list of open research problems and future research directions.

Key facts. Cited by 48 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jun 2019.

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Citing papers per year: 2021: 17; 2022: 9; 2023: 8; 2024: 3; 2025: 6; 2026: 5.

48 papers.

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  1. 2021Learning to Optimize: A Primer and A Benchmarkcited by 206
  2. 2023Learning to Warm-Start Fixed-Point Optimization Algorithmscited by 32
  3. 2022Symbolic Learning to Optimize: Towards Interpretability and Scalabilitycited by 16
  4. 2021Learning to Continuously Optimize Wireless Resource in a Dynamic Environment: A Bilevel Optimization Perspectivecited by 12
  5. 2022Efficient Deep Unfolding for SISO-OFDM Channel Estimationcited by 8
  6. 2023Message Passing Meets Graph Neural Networks: A New Paradigm for Massive MIMO Systemscited by 8
  7. 2021Model-Based Machine Learning for Communicationscited by 7
  8. 2021LoRD-Net: Unfolded Deep Detection Network with Low-Resolution Receiverscited by 7
  9. 2021Joint Deep Reinforcement Learning and Unfolding: Beam Selection and Precoding for mmWave Multiuser MIMO with Lens Arrayscited by 6
  10. 2023Deep Graph Unfolding for Beamforming in MU-MIMO Interference Networkscited by 6
  11. 2021FAID Diversity via Neural Networkscited by 5
  12. 2021Algorithm Unrolling for Massive Access via Deep Neural Network with Theoretical Guaranteecited by 5
36 more
  1. 2022Graph-based Algorithm Unfolding for Energy-aware Power Allocation in Wireless Networkscited by 5
  2. 2022Bit Error and Block Error Rate Training for ML-Assisted Communicationcited by 5
  3. 2024Data-Driven Performance Guarantees for Classical and Learned Optimizerscited by 5
  4. 2021Unrolling Particles: Unsupervised Learning of Sampling Distributionscited by 4
  5. 2022FedCau: A Proactive Stop Policy for Communication and Computation Efficient Federated Learningcited by 4
  6. 2021Phase Retrieval using Expectation Consistent Signal Recovery Algorithm based on Hypernetworkcited by 3
  7. 2021CMDNet: Learning a Probabilistic Relaxation of Discrete Variables for Soft Detection with Low Complexitycited by 3
  8. 2021Learn to Communicate with Neural Calibration: Scalability and Generalizationcited by 3
  9. 2023Optimization Guarantees of Unfolded ISTA and ADMM Networks With Smooth Soft-Thresholdingcited by 3
  10. 2022DDPG-Driven Deep-Unfolding with Adaptive Depth for Channel Estimation with Sparse Bayesian Learningcited by 2
  11. 2022Progressive Fusion for Multimodal Integrationcited by 2
  12. 2026Scalable Deep Unfolding of Conic Optimizerscited by 2
  13. 2021Reservoir-Based Distributed Machine Learning for Edge Operationcited by 1
  14. 2021A Design Space Study for LISTA and Beyondcited by 1
  15. 2021Photothermal-SR-Net: A Customized Deep Unfolding Neural Network for Photothermal Super Resolution Imagingcited by 1
  16. 2021Adversarial Neural Networks for Error Correcting Codescited by 1
  17. 2022DUIDD: Deep-Unfolded Interleaved Detection and Decoding for MIMO Wireless Systemscited by 1
  18. 2023SICNN: Soft Interference Cancellation Inspired Neural Network Equalizerscited by 1
  19. 2025Joint Transmit and Pinching Beamforming for Pinching Antenna Systems (PASS): Optimization-Based or Learning-Based?cited by 1
  20. 2025Deep-Unfolded Massive Grant-Free Transmission in Cell-Free Wireless Communication Systemscited by 1
  21. 2026CPCANet: Deep Unfolding Common Principal Component Analysis for Domain Generalizationcited by 1
  22. 2021Signal Processing Based Deep Learning for Blind Symbol Decoding and Modulation Classificationcited by 0
  23. 2021Reservoir Based Edge Training on RF Data To Deliver Intelligent and Efficient IoT Spectrum Sensorscited by 0
  24. 2022MetaSSD: Meta-Learned Self-Supervised Detectioncited by 0
  25. 2023Hubbard-Stratonovich Detector for Simple Trainable MIMO Signal Detectioncited by 0
  26. 2023Deep Unfolded Simulated Bifurcation for Massive MIMO Signal Detectioncited by 0
  27. 2023Improving Federated Aggregation with Deep Unfolding Networkscited by 0
  28. 2024Transfer-based Adversarial Poisoning Attacks for Online (MIMO-)Deep Recevierscited by 0
  29. 2024Differentiable High-Order Markov Models for Spectrum Predictioncited by 0
  30. 2025Transfer Learning for Deep-Unfolded Combinatorial Optimization Solver with Quantum Annealercited by 0
  31. 2025Learning to Optimally Dispatch Power: Performance on a Nation-Wide Real-World Datasetcited by 0
  32. 2025Multi-beam Beamforming in RIS-aided MIMO Subject to Reradiation Mask Constraints -- Optimization and Machine Learning Designcited by 0
  33. 2025Deep Unfolding for MIMO Signal Detectioncited by 0
  34. 2026Neural Ising Machines via Unrolling and Zeroth-Order Trainingcited by 0
  35. 2026Auto-Unrolled Proximal Gradient Descent: An AutoML Approach to Interpretable Waveform Optimizationcited by 0
  36. 2026Deep Unfolded Latent Optimally Partitioned-l2/l1 Networks for Data-driven Block-Sparse Recoverycited by 0