mlsanityData to 14 Oct 2026

UAV-assisted Joint Mobile Edge Computing and Data Collection via Matching-enabled Deep Reinforcement Learning

arXiv 2502.07388 ↗First posted 11 Feb 2025cs.NEcited by 2

On the map: Deep reinforcement learning methods → RL for robot navigation and UAV control

Abstract (arXiv)

Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) and data collection (DC) have been popular research issues. Different from existing works that consider MEC and DC scenarios separately, this paper investigates a multi-UAV-assisted joint MEC-DC system. Specifically, we formulate a joint optimization problem to minimize the MEC latency and maximize the collected data volume. This problem can be classified as a non-convex mixed integer programming problem that exhibits long-term optimization and dynamics. Thus, we propose a deep reinforcement learning-based approach that jointly optimizes the UAV movement, user transmit power, and user association in real time to solve the problem efficiently. Specifically, we reformulate the optimization problem into an action space-reduced Markov decision process (MDP) and optimize the user association by using a two-phase matching-based association (TMA) strategy. Subsequently, we propose a soft actor-critic (SAC)-based approach that integrates the proposed TMA strategy (SAC-TMA) to solve the formulated joint optimization problem collaboratively. Simulation results demonstrate that the proposed SAC-TMA is able to coordinate the two subsystems and can effectively reduce the system latency and improve the data collection volume compared with other benchmark algorithms.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in RL for robot navigation and UAV control, one of 15 directions in Deep reinforcement learning methods. Builds on 14 of its 62 references that are in the map. First posted on arXiv 11 Feb 2025.

Builds on

14 of 62 references.

References · 14

  1. 2017Proximal Policy Optimization Algorithmscited by 15,215
  2. 2018Addressing Function Approximation Error in Actor-Critic Methodscited by 2,417
  3. 2018Soft Actor-Critic Algorithms and Applicationscited by 1,240
  4. 2023A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applicationscited by 27
  5. 2020A Comprehensive Overview on 5G-and-Beyond Networks with UAVs: From Communications to Sensing and Intelligencecited by 21
  6. 2024Multi-objective Aerial Collaborative Secure Communication Optimization via Generative Diffusion Model-enabled Deep Reinforcement Learningcited by 16
  7. 2023Joint Task Offloading and Resource Allocation in Aerial-Terrestrial UAV Networks with Edge and Fog Computing for Post-Disaster Rescuecited by 14
  8. 2024Multi-objective Optimization for Multi-UAV-assisted Mobile Edge Computingcited by 10
  9. 2023UAV Swarm-enabled Collaborative Secure Relay Communications with Time-domain Colluding Eavesdroppercited by 5
  10. 2024TJCCT: A Two-timescale Approach for UAV-assisted Mobile Edge Computingcited by 4
  11. 2019Energy-Constrained UAV Data Collection Systems: NOMA and OMAcited by 3
  12. 2023Robust Computation Offloading and Trajectory Optimization for Multi-UAV-Assisted MEC: A Multi-Agent DRL Approachcited by 3
2 more
  1. 2024Multi-objective Optimization for Data Collection in UAV-assisted Agricultural IoTcited by 1
  2. 2024Dual UAV Cluster-Assisted Maritime Physical Layer Secure Communications via Collaborative Beamformingcited by 1

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Cited by year

Citing papers per year: 2025: 2.

2 papers.

  1. 2025Joint Link Adaptation and Device Scheduling Approach for URLLC Industrial IoT Network: A DRL-based Method with Bayesian Optimizationcited by 1
  2. 2025Joint Task Offloading and Resource Allocation in Low-Altitude MEC via Graph Attention Diffusioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Energy Efficient Task Offloading in UAV-Enabled MEC Using a Fully Decentralized Deep Reinforcement Learning Approach
  2. 2025Task Delay and Energy Consumption Minimization for Low-altitude MEC via Evolutionary Multi-objective Deep Reinforcement Learning
  3. 2024Deep progressive reinforcement learning-based flexible resource scheduling framework for IRS and UAV-assisted MEC system
  4. 2026Collaborative Computation and Migration in Multi-UAV Networks with Semantic Communication ↗
  5. 2025Joint Resource Management for Energy-efficient UAV-assisted SWIPT-MEC: A Deep Reinforcement Learning Approach
  6. 2025Hierarchical Task Offloading for UAV-Assisted Vehicular Edge Computing via Deep Reinforcement Learning
  7. 2026Joint Trajectory, RIS, and Computation Offloading Optimization via Decentralized Model-Based PPO in Urban Multi-UAV Mobile Edge Computing
  8. 2024Maximizing User Connectivity in AI-Enabled Multi-UAV Networks: A Distributed Strategy Generalized to Arbitrary User Distributions