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<p>The explosive growth of mobile users (MUs) has led to a substantial increase in computing tasks being offloaded to MEC, bringing tremendous pressure to the sustainable development of MEC. To address this problem, the integration of multi-base station (BS) with MEC has attracted widespread attention. In this paper, we propose the joint optimization problem of resource allocation, computation offloading, and resource pricing for multi-BS cooperative MEC in heterogeneous multicell networks. We model the interactions between MEC server, macro base station (MBS), femto base station (FBS), and MUs as a four-stage Stackelberg game, and derive the equilibrium resource pricing and allocation strategies. In the first three stages, we focus on devising optimal resource allocation and pricing strategies to maximize the utility of all stakeholders. In the fourth stage, MUs make an offloading decision to maximize their utility based on the different pricing strategies. The optimization problems in each stage are simplified and proved by derivation using backward induction method. Our approach offers a novel strategy by effectively integrating multiple BSs, enabling a more flexible and efficient resource distribution. The simulation results demonstrate that the proposed multi-BS model can improve the utilities of MBS and MUs by 53% and 50% respectively by introducing FBS.</p>

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Computation offloading and pricing strategy for heterogeneous multicell network with mobile edge computing

  • 期刊论文

  • 发表日期：

    2025年2月19日

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  • Minli Chen,
  • Yifeng Zheng,
  • Jingmin Yang,
  • Liwei Yang,
  • Wenjie Zhang

摘要

The explosive growth of mobile users (MUs) has led to a substantial increase in computing tasks being offloaded to MEC, bringing tremendous pressure to the sustainable development of MEC. To address this problem, the integration of multi-base station (BS) with MEC has attracted widespread attention. In this paper, we propose the joint optimization problem of resource allocation, computation offloading, and resource pricing for multi-BS cooperative MEC in heterogeneous multicell networks. We model the interactions between MEC server, macro base station (MBS), femto base station (FBS), and MUs as a four-stage Stackelberg game, and derive the equilibrium resource pricing and allocation strategies. In the first three stages, we focus on devising optimal resource allocation and pricing strategies to maximize the utility of all stakeholders. In the fourth stage, MUs make an offloading decision to maximize their utility based on the different pricing strategies. The optimization problems in each stage are simplified and proved by derivation using backward induction method. Our approach offers a novel strategy by effectively integrating multiple BSs, enabling a more flexible and efficient resource distribution. The simulation results demonstrate that the proposed multi-BS model can improve the utilities of MBS and MUs by 53% and 50% respectively by introducing FBS.