LEO-RAN切片场景联合用户关联和动态资源分配算法

doi:10.11959/j.issn.1000-436x.2024041

通信学报 ›› 2024, Vol. 45 ›› Issue (2): 173-187.doi: 10.11959/j.issn.1000-436x.2024041

• 学术论文 • 上一篇

LEO-RAN切片场景联合用户关联和动态资源分配算法

陈赓¹, 邢治薇¹, 沈斐², 曾庆田¹

¹ 山东科技大学电子信息工程学院，山东青岛 266590
² 中国科学院上海微系统与信息技术研究所，上海 200050

修回日期:2023-12-26 出版日期:2024-02-01 发布日期:2024-02-01
作者简介:陈赓（1984− ），男，山东潍坊人，博士，山东科技大学副教授、硕士生导师，主要研究方向为异构网络、泛在网络和软件定义移动网络方面的无线资源管理和优化算法
邢治薇（1996− ），女，山东日照人，山东科技大学硕士生，主要研究方向为网络切片、资源分配
沈斐（1983− ），女，江苏南京人，博士，中国科学院上海微系统与信息技术研究所研究员、博士生导师，主要研究方向为无线通信、边缘计算和雾计算的资源优化
曾庆田（1976− ），男，山东潍坊人，博士，山东科技大学教授、博士生导师，主要研究方向为 Petri网、过程挖掘和知识管理
基金资助:
国家自然科学基金资助项目(61701284);山东省自然科学基金资助项目(ZR2022MF226);山东科技大学青年教师人才培养计划基金资助项目(BJ20221101);青岛市应用基础研究计划基金资助项目(19-6-2-1-cg);山东科技大学菁英计划基金资助项目(skr21-3-B-048);中国科学院百人计划基金资助项目(E06BRA1001);山东省泰山学者计划基金资助项目(ts20190936)

Joint user association and dynamic resource allocation algorithm for LEO-RAN slicing scenarios

Geng CHEN¹, Zhiwei XING¹, Fei SHEN², Qingtian ZENG¹

¹ College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao 266590, China
² Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China

Revised:2023-12-26 Online:2024-02-01 Published:2024-02-01
Supported by:
The National Natural Science Foundation of China(61701284);The Natural Science Foundation of Shan-dong Province(ZR2022MF226);The Talented Young Teachers Training Program of Shandong University of Science and Tech-nology(BJ20221101);The Innovative Research Foundation of Qingdao(19-6-2-1-cg);The Elite Plan Project of Shandong University of Science and Technology(skr21-3-B-048);The Hundred Talent Program of Chinese Academy of Sciences(E06BRA1001);The Taishan Scholar Program of Shandong Province(ts20190936)

摘要/Abstract

摘要：

为了解决6G天地一体化网络的资源高效利用问题，提出了一种面向高密度低地球轨道卫星-无线接入网（LEO-RAN）切片场景的联合用户关联和动态资源分配算法。考虑不同切片的最小速率、最大时延及资源比例等约束，以频谱效率（SE）和不同切片服务水平协议（SLA）满意率（SSR）的加权和作为优化目标，建立用户关联和资源分配的联合优化问题。首先设计基于多智能体深度确定性策略梯度（MADDPG）的网络切片算法确定切片资源比例，然后采用基于拉格朗日对偶的用户关联算法确定最优的用户关联策略，最后通过轮询调度机制将资源分配给用户。仿真结果表明，所提算法在满足不同切片差异化 SLA 的同时能够有效提高 SE。与基于MADDPG-RA、MATD3-LG、MATD3-RA、MASAC-LG和MASAC-RA算法相比，所提算法系统效用分别提升了2.0%、2.3%、5.7%、8.7%和9.4%。

关键词: LEO卫星通信, 网络切片, 用户关联, 多智能体深度确定性策略梯度, 系统效用

Abstract:

A joint user association and dynamic resource allocation algorithm was proposed for the slicing scenario of ultra dense low earth orbit-radio access network (LEO-RAN) in order to address the efficient utilization of resources of the integrated terrestrial-satellite network for 6G .Considering the constraints of the minimum rate, maximum delay and resource proportion of different slices, a joint optimization problem of user association and resource allocation was established to maximize the weighted sum of the SE and the differentiated SLA of different slices as the optimization objective.A network slicing algorithm based on multi-agent deep deterministic policy gradient (MADDPG) was proposed to determine the proportion of slicing resources, a Lagrange dual based user association algorithm was proposed to determine the optimal user association policy and the resources were allocated to users by using the round-robin scheduling mechanism.The simulation results show that the proposed algorithm can effectively improve SE while satisfying the differentiated SLA of different slices.Compared with MADDPG-RA, MATD3-LG, MATD3-RA, MASAC-LG and MASAC-RA algorithms, the system utility of the proposed algorithm is improved by 2.0%, 2.3%, 5.7%, 8.7% and 9.4%, respectively.

Key words: LEO satellite communication, network slicing, user association, MADDPG, system utility

中图分类号:

TN929.5

陈赓, 邢治薇, 沈斐, 曾庆田. LEO-RAN切片场景联合用户关联和动态资源分配算法[J]. 通信学报, 2024, 45(2): 173-187.

Geng CHEN, Zhiwei XING, Fei SHEN, Qingtian ZENG. Joint user association and dynamic resource allocation algorithm for LEO-RAN slicing scenarios[J]. Journal on Communications, 2024, 45(2): 173-187.

图/表 16

图1

表1

主要符号和变量"

参数	含义	参数	含义
$M$	基站集合	f	切片资源分配比例集合
$L$	LEO卫星集合	z	用户资源比例集合
$B$	STBS集合	x	用户关联集合
$T$	时隙集合	$Γ_{u b}$	用户的可实现速率
$N$	切片集合	$R_{u_{b}^{n}}$	用户的速率
$U_{n}$	切片中用户的集合	w	负载均衡效用函数
$U_{b}^{n}$	切片n中与STBSb关联的用户集合	$λ_{n b}$	STBS b中切片n的拉格朗日乘子
$q_{u_{b}^{n}_{, t}}^{tran}$	用户 $u_{b}^{n}$ 的传输队列	k	算法1中的迭代次数
$q_{u_{b,}^{n}_{i}}^{tran}$	用户 $u_{b}^{n}$ 的传输时延	$δ (k)$	动态步长

表1

图2

表2

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参数		VoLTE参数值	eMBB参数值	URLLC参数值
轮询调度/ms		0.5	0.5	0.5
用户数量/个		333	667	1 000
数据包请求到达间隔分布		均匀分布	截断帕累托分布	指数分布
		[min=0, max=160 ms]	[指数分布=1.2, mean=6 ms, max=12.5 ms]	[mean=180 ms]
数据包的大小分布		40 B	[截断帕累托分布=1.2, mean=100 B, max=250 B]	0.15 MB
切片要求	速率	51 kbit/s	100 Mbit/s	10 Mbit/s
	时延/ms	10	10	3

LEO-RAN切片场景联合用户关联和动态资源分配算法

Joint user association and dynamic resource allocation algorithm for LEO-RAN slicing scenarios

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