基于移动边缘计算的NOMA异构网络资源分配

张海君; 张资政; 隆克平

doi:10.11959/j.issn.1000-436x.2020069

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基于移动边缘计算的NOMA异构网络资源分配

专题：边缘计算关键技术 | 更新时间：2024-06-05

- 基于移动边缘计算的NOMA异构网络资源分配
- Resource allocation in NOMA heterogeneous network based on MEC
- 通信学报 2020年41卷第4期页码：27-33
- 作者机构：
  
  北京科技大学计算机与通信工程学院，北京 100083
- 作者简介：
  
  [ "张海君（1986- ），男，辽宁朝阳人，博士，北京科技大学教授，主要研究方向为6G移动通信、人工智能与无线网络、机器学习与大数据等" ]
  [ "张资政（1996- ），男，山东临沂人，北京科技大学硕士生，主要研究方向为边缘计算、新一代无线通信等" ]
  [ "隆克平（1968- ），男，四川通江人，博士，北京科技大学教授，主要研究方向为新一代网络技术、光互联网关键技术、无线通信技术、人工智能与大数据" ]
- 基金信息：
  
  国家优秀青年科学基金资助项目(61822104);国家自然科学基金资助项目(61771044)
- DOI：10.11959/j.issn.1000-436x.2020069
  中图分类号： TN92
- 网络首发：2020-04，
  
  纸质出版：2020-04-25
- 稿件说明：
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张海君, 张资政, 隆克平. 基于移动边缘计算的NOMA异构网络资源分配[J]. 通信学报, 2020,41(4):27-33.

Haijun ZHANG, Zizheng ZHANG, Keping LONG. Resource allocation in NOMA heterogeneous network based on MEC[J]. Journal on Communications, 2020, 41(4): 27-33.
张海君, 张资政, 隆克平. 基于移动边缘计算的NOMA异构网络资源分配[J]. 通信学报, 2020,41(4):27-33. DOI： 10.11959/j.issn.1000-436x.2020069.

Haijun ZHANG, Zizheng ZHANG, Keping LONG. Resource allocation in NOMA heterogeneous network based on MEC[J]. Journal on Communications, 2020, 41(4): 27-33. DOI： 10.11959/j.issn.1000-436x.2020069.

摘要

以最大化缓存收益为目标，针对部署缓存的 NOMA 异构网络下的基站用户匹配及功率分配问题，结合消息传递及 DC 规划提出了 NOMA 联合优化算法。首先将约束条件合并到目标函数中，通过计算新的优化问题中函数节点与变量节点间消息传递的边缘得到用户协同结果；然后将原优化问题变形为2个凸函数差的形式，通过DC规划对功率资源进行分配；最后迭代计算得到最终的用户协同及功率分配结果。仿真结果证明所提算法有效地提升了网络性能。

Abstract

Aiming at maximizing the cache revenue

a joint user association and power allocation algorithm was proposed for the matching of base stations with users and power allocation in a NOMA heterogeneous network with caches

a NOMA joint optimization algorithm which was achieved by combing with message passing and DC programming was proposed.First

the constraints were incorporated into the objective function

and the user association result was obtained by calculating the marginal of the message passing between the function node and the variable node in the new optimization problem.Then

the original optimization problem was transformed into the form of the difference between two convex functions

and allocate power resources through DC programming.Finally

the final user association and power allocation results are obtained through iterative calculations.Simulation results prove that the proposed algorithm effectively improves network performance.

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Keywords

references

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