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<p>Due to the variety of communication services coexistence and the improvement of infrastructure, the next-generation network architecture will become more heterogeneous, with unmanned aerial vehicle (UAV), device-to-device (D2D) communication, and mobile edge computing (MEC) all playing significant roles in 6G networks. Considering the challenges brought by the coexistence of network demands, this paper proposes a heterogeneous edge computing network that integrates UAV-aided MEC and D2D communication sharing, where multiple users offload computing tasks to MEC via mobile UAVs, while D2D users engage in information exchange over shared spectrum. To enhance resource utilization, a Stackelberg game-based power allocation scheme is proposed, where the UAV, acting as the leader, receives rewards based on the user offloading rate, while the D2D transmitter, acting as the follower, obtains rewards based on the communication rate of the receiver, provided that the UAV interference threshold is met. The Nash equilibrium solution was analyzed and solved using backward induction, and the power allocation and UAV path planning problem were solved using continuous convex approximation and alternating optimization algorithms. Simulation results show that the proposed scheme can effectively reduce system energy consumption and achieve relatively satisfactory average offloading rates and average communication rates for both offloading users and D2D users.</p>

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Resource Allocation and Trajectory Optimization for UAV-Aided Heterogeneous Mobile Edge Computing Networks

  • 期刊论文

  • 发表日期：

    2025年8月26日

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  • Chunling Peng,
  • Tingting Chen,
  • Bin Tang,
  • Yuanzhu Lü

摘要

Due to the variety of communication services coexistence and the improvement of infrastructure, the next-generation network architecture will become more heterogeneous, with unmanned aerial vehicle (UAV), device-to-device (D2D) communication, and mobile edge computing (MEC) all playing significant roles in 6G networks. Considering the challenges brought by the coexistence of network demands, this paper proposes a heterogeneous edge computing network that integrates UAV-aided MEC and D2D communication sharing, where multiple users offload computing tasks to MEC via mobile UAVs, while D2D users engage in information exchange over shared spectrum. To enhance resource utilization, a Stackelberg game-based power allocation scheme is proposed, where the UAV, acting as the leader, receives rewards based on the user offloading rate, while the D2D transmitter, acting as the follower, obtains rewards based on the communication rate of the receiver, provided that the UAV interference threshold is met. The Nash equilibrium solution was analyzed and solved using backward induction, and the power allocation and UAV path planning problem were solved using continuous convex approximation and alternating optimization algorithms. Simulation results show that the proposed scheme can effectively reduce system energy consumption and achieve relatively satisfactory average offloading rates and average communication rates for both offloading users and D2D users.