Deep Learning Power Allocation in Massive MIMO
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Abstract (arXiv)
This work advocates the use of deep learning to perform max-min and max-prod power allocation in the downlink of Massive MIMO networks. More precisely, a deep neural network is trained to learn the map between the positions of user equipments (UEs) and the optimal power allocation policies, and then used to predict the power allocation profiles for a new set of UEs' positions. The use of deep learning significantly improves the complexity-performance trade-off of power allocation, compared to traditional optimization-oriented methods. Particularly, the proposed approach does not require the computation of any statistical average, which would be instead necessary by using standard methods, and is able to guarantee near-optimal performance.
Key facts. Cited by 13 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Dec 2018.
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Citing papers per year: 2021: 7; 2022: 3; 2023: 1; 2024: 1; 2025: 1.
13 papers.
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- 2021Adversarial Attacks on Deep Learning Based Power Allocation in a Massive MIMO Networkcited by 11
- 2022Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examplescited by 5
- 2021Deep Learning-based Power Control for Cell-Free Massive MIMO Networkscited by 4
- 2021Adversarial Attacks against Deep Learning Based Power Control in Wireless Communicationscited by 4
- 2021Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO Systemcited by 3
- 2022Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Trainingcited by 1
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Frameworkcited by 1
- 2025To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networkscited by 1
- 2021Learning to Perform Downlink Channel Estimation in Massive MIMO Systemscited by 0
- 2021Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systemscited by 0
- 2021Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systemscited by 0
- 2022A Review of the Convergence of 5G/6G Architecture and Deep Learningcited by 0
- 2025To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks23 Jul 2025
- 2024Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifiers11 Apr 2024
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework16 May 2023
- 2022A Review of the Convergence of 5G/6G Architecture and Deep Learning16 Aug 2022
- 2022Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples4 Jul 2022
- 2022Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Training14 Jun 2022
- 2021Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems29 Dec 2021
- 2021Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systems18 Oct 2021
- 2021Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO System10 Oct 2021
- 2021Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications16 Sep 2021
- 2021Learning to Perform Downlink Channel Estimation in Massive MIMO Systems6 Sep 2021
- 2021Deep Learning-based Power Control for Cell-Free Massive MIMO Networks20 Feb 2021
- 2021Adversarial Attacks on Deep Learning Based Power Allocation in a Massive MIMO Networkcited by 11
- 2022Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examplescited by 5
- 2021Deep Learning-based Power Control for Cell-Free Massive MIMO Networkscited by 4
- 2021Adversarial Attacks against Deep Learning Based Power Control in Wireless Communicationscited by 4
- 2021Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO Systemcited by 3
- 2022Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Trainingcited by 1
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Frameworkcited by 1
- 2025To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networkscited by 1
- 2021Learning to Perform Downlink Channel Estimation in Massive MIMO Systemscited by 0
- 2021Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systemscited by 0
- 2021Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systemscited by 0
- 2022A Review of the Convergence of 5G/6G Architecture and Deep Learningcited by 0
12 most cited of 13 All 13 (JSON)
- 2025To Trust or Not to Trust: On Calibration in ML-based Resource Allocation for Wireless Networks23 Jul 2025
- 2024Adversarial Robustness of Distilled and Pruned Deep Learning-based Wireless Classifiers11 Apr 2024
- 2023Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework16 May 2023
- 2022A Review of the Convergence of 5G/6G Architecture and Deep Learning16 Aug 2022
- 2022Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples4 Jul 2022
- 2022Downlink Power Allocation in Massive MIMO via Deep Learning: Adversarial Attacks and Training14 Jun 2022
- 2021Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems29 Dec 2021
- 2021Deep Learning-Based Power Control for Uplink Cell-Free Massive MIMO Systems18 Oct 2021
- 2021Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO System10 Oct 2021
- 2021Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications16 Sep 2021
- 2021Learning to Perform Downlink Channel Estimation in Massive MIMO Systems6 Sep 2021
- 2021Deep Learning-based Power Control for Cell-Free Massive MIMO Networks20 Feb 2021
12 newest of 13 All 13 (JSON)