mlsanityData to 7 Oct 2026

Deep-Reinforcement Learning Multiple Access for Heterogeneous Wireless Networks

arXiv 1712.00162 ↗First posted 1 Dec 2017cs.NIcited by 37

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Abstract (arXiv)

This paper investigates the use of deep reinforcement learning (DRL) in a MAC protocol for heterogeneous wireless networking referred to as Deep-reinforcement Learning Multiple Access (DLMA). The thrust of this work is partially inspired by the vision of DARPA SC2, a 3-year competition whereby competitors are to come up with a clean-slate design that "best share spectrum with any network(s), in any environment, without prior knowledge, leveraging on machine-learning technique". Specifically, this paper considers the problem of sharing time slots among a multiple of time-slotted networks that adopt different MAC protocols. One of the MAC protocols is DLMA. The other two are TDMA and ALOHA. The nodes operating DLMA do not know that the other two MAC protocols are TDMA and ALOHA. Yet, by a series of observations of the environment, its own actions, and the resulting rewards, a DLMA node can learn an optimal MAC strategy to coexist harmoniously with the TDMA and ALOHA nodes according to a specified objective (e.g., the objective could be the sum throughput of all networks, or a general alpha-fairness objective).

Key facts. Cited by 37 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Dec 2017.

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Citing papers per year: 2021: 11; 2022: 5; 2023: 10; 2024: 4; 2025: 3; 2026: 4.

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  1. 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimizationcited by 56
  2. 2021Applications of deep learning in traffic congestion detection, prediction and alleviation: A surveycited by 14
  3. 2023Holistic Network Virtualization and Pervasive Network Intelligence for 6Gcited by 14
  4. 2022A new hope for network model generalizationcited by 11
  5. 20213D UAV Trajectory and Data Collection Optimisation via Deep Reinforcement Learningcited by 8
  6. 2021Cooperative Multi-Agent Reinforcement Learning Based Distributed Dynamic Spectrum Access in Cognitive Radio Networkscited by 7
  7. 2023Multi-Flow Transmission in Wireless Interference Networks: A Convergent Graph Learning Approachcited by 6
  8. 2021Towards Multi-agent Reinforcement Learning for Wireless Network Protocol Synthesiscited by 4
  9. 2021Dynamic Multichannel Access via Multi-agent Reinforcement Learning: Throughput and Fairness Guaranteescited by 4
  10. 2024Multiple Access in the Era of Distributed Computing and Edge Intelligencecited by 4
  11. 2021Can You Fix My Neural Network? Real-Time Adaptive Waveform Synthesis for Resilient Wireless Signal Classificationcited by 3
  12. 2025Consensus-based Decentralized Multi-agent Reinforcement Learning for Random Access Network Optimizationcited by 3
25 more
  1. 2023Self-Sustaining Multiple Access with Continual Deep Reinforcement Learning for Dynamic Metaverse Applicationscited by 2
  2. 2021Distributed Deep Reinforcement Learning for Collaborative Spectrum Sharingcited by 1
  3. 2021Medium Access using Distributed Reinforcement Learning for IoTs with Low-Complexity Wireless Transceiverscited by 1
  4. 2021Medium Access Control protocol for Collaborative Spectrum Learning in Wireless Networkscited by 1
  5. 2022Distributed Transmission Control for Wireless Networks using Multi-Agent Reinforcement Learningcited by 1
  6. 2022Learning-based Autonomous Channel Access in the Presence of Hidden Terminalscited by 1
  7. 2022Deep Reinforcement Learning for Power Control in Next-Generation WiFi Network Systemscited by 1
  8. 2023Generalization of Deep Reinforcement Learning for Jammer-Resilient Frequency and Power Allocationcited by 1
  9. 2024Dynamic Spectrum Access for Ambient Backscatter Communication-assisted D2D Systems with Quantum Reinforcement Learningcited by 1
  10. 2021Detection of Insider Attacks in Distributed Projected Subgradient Algorithmscited by 0
  11. 2021Fundamental Limits of Reinforcement Learning in Environment with Endogeneous and Exogeneous Uncertaintycited by 0
  12. 2022AI-aided Traffic Control Scheme for M2M Communications in the Internet of Vehiclescited by 0
  13. 2023Reinforcement Learning for Protocol Synthesis in Resource-Constrained Wireless Sensor and IoT Networkscited by 0
  14. 2023Evolution of MAC Protocols in the Machine Learning Decade: A Comprehensive Surveycited by 0
  15. 2023Sparsity-Aware Intelligent Massive Random Access Control in Open RAN: A Reinforcement Learning Based Approachcited by 0
  16. 2023FAIRO: Fairness-aware Adaptation in Sequential-Decision Making for Human-in-the-Loop Systemscited by 0
  17. 2023FinA: Fairness of Adverse Effects in Decision-Making of Human-Cyber-Physical-Systemcited by 0
  18. 2024Prioritized League Reinforcement Learning for Large-Scale Heterogeneous Multiagent Systemscited by 0
  19. 2024Neural Network-Based Bandit: A Medium Access Control for the IIoT Alarm Scenariocited by 0
  20. 2025Fair Dynamic Spectrum Access via Fully Decentralized Multi-Agent Reinforcement Learningcited by 0
  21. 2025Causal Model-Based Reinforcement Learning for Sample-Efficient IoT Channel Accesscited by 0
  22. 2026Optimal Power Allocation and Sub-Optimal Channel Assignment for Downlink NOMA Systems Using Deep Reinforcement Learningcited by 0
  23. 2026Plan2Cleanse: Test-Time Backdoor Defense via Monte-Carlo Planning in Deep Reinforcement Learningcited by 0
  24. 2026KISS: Keeping it Simple and Slotted when Learning to Communicate over Wirelesscited by 0
  25. 2026Channel-Token Attention for Reliable Dynamic Spectrum Access under Bursty Primary-User Trafficcited by 0