混合D2D蜂窝网络中基于模拟退火算法的资源调度策略

doi:10.11959/j.issn.1000-0801.2017093

电信科学 ›› 2017, Vol. 33 ›› Issue (4): 71-77.doi: 10.11959/j.issn.1000-0801.2017093

混合D2D蜂窝网络中基于模拟退火算法的资源调度策略

余翔,张海波,杨路

重庆邮电大学，重庆 400065

修回日期:2017-03-17 出版日期:2017-04-01 发布日期:2017-04-26
作者简介:余翔（1969-），男，重庆邮电大学通信与信息工程学院副教授，主要研究方向为通信网及交换技术、计算机网络及信息安全和下一代网络技术。|张海波（1990-），男，重庆邮电大学硕士生，主要研究方向为D2D通信的资源分配与功率控制。|杨路（1969-），女，重庆邮电大学通信与信息工程学院高级工程师，主要研究方向为通信网及交换技术、计算机网络及信息安全、下一代网络技术。
基金资助:
国家科技重大专项基金资助项目(2015ZX03004004)

Resource scheduling strategy based on simulated annealing algorithm in hybrid D2D cellular networks

Xiang YU,Haibo ZHANG,Lu YANG

Chongqing University of Posts and Telecommunications,Chongqing 400065,China

Revised:2017-03-17 Online:2017-04-01 Published:2017-04-26
Supported by:
National Science and Technology Major Project(2015ZX03004004)

摘要/Abstract

摘要：

D2D 通信是未来5G 网络中一种近距离直通通信方式，在通信过程中，信息直接由发送端传给接收用户，而不需要经过基站的转发。在传统蜂窝网络中引入D2D通信可以极大地提升系统的总吞吐量、增大频谱资源的利用率以及降低发射终端的功耗。主要介绍了一种适用于混合D2D蜂窝网络中的资源分配方法，通过拉格朗日乘子法结合模拟退火算法实现频谱资源的分配，提出一种同时考虑信道容量和能耗的基于模拟退火算法的资源调度策略。本算法在维也纳仿真平台上经仿真验证，相比于传统贪婪优化算法，可以明显增大系统总吞吐量和频谱资源利用率。另外，算法中采用了分布式资源调度方法，D2D 用户根据算法步骤自行搜索适合的目标信道并计算其发射功率，可以有效减少基站的信令开销。

关键词: D2D通信, 资源分配, 拉格朗日乘子法, 模拟退火算法, 功率控制

Abstract:

D2D communication is a short distance communication mode in the future 5G network.In the process of communication,the information is transmitted from the sender to the receiver directly,without the need to transmit through the base station.The introduction of D2D communication in the traditional cellular network can greatly improve the total throughput of the system,increase the utilization of spectrum resources and reduce the power consumption of the transmitter.A resource allocation method which was used in hybrid D2D cellular network was mainly introduced,spectrum resources was distributed by Lagrange multiplier method combined with simulated annealing algorithm,a consideration of channel capacity and energy consumption of the resource scheduling strategy based on simulated annealing algorithm was put forward.This algorithm was simulated by the simulation platform in Vienna,compared to the traditional greedy optimization algorithm,it can significantly increase the total system throughput and bandwidth utilization and reduce the power consumption.In addition,the distributed algorithm was adopted,that D2D users searched for a suitable target channel and calculated their transmit power according to the algorithm steps,which reduced the signaling overhead of the base station.

Key words: D2D communication, resource allocation, Lagrange multiplier method, simulated annealing algorithm, power control

中图分类号:

TN929.5

余翔,张海波,杨路. 混合D2D蜂窝网络中基于模拟退火算法的资源调度策略[J]. 电信科学, 2017, 33(4): 71-77.

Xiang YU,Haibo ZHANG,Lu YANG. Resource scheduling strategy based on simulated annealing algorithm in hybrid D2D cellular networks[J]. Telecommunications Science, 2017, 33(4): 71-77.

图/表 7

图1

图2

表1

图3

图4

图5

图6

参考文献 15

[1]	LI Y B , GUO Z H , XU L X . Dynamic joint resource allocation for device-to-device communication based on inference control in cellular networks[J]. Fire Control ＆ Command Control, 2016,41(1).
[2]	GU J , BAE S J , CHOI B G , et al. Dynamic power control mechanism for interference coor dination of device-to-device communication in cellular networks[C]// 2011 Third International Conference on Ubiquitous and Future Networks(ICUFN), June15-17,2011, Dalian,China. New Jersey: IEEE Press, 2011:71-75.
[3]	JANIS P , KOIVUNEN V , RIBEIRO C , et al. Interference-aware resource allocation for device-to-device radio underlaying cellular network[C]// VTC Spring 2009-IEEE 69th Vehicular Technology Conference, April26-19,2009, Barcelona,Spain. New Jersey: IEEE Press, 2009:1-5.
[4]	RONG T , WU B , MI Z K . A resource sharing algorithm for D2D communicationwithin LTE networks[J]. Journal of Nanjing University of Posts and Telecommunications(Natural Science), 2013,33(3).
[5]	ZULHASNINE M , HUANG C C , SRINIVASAN A , et al. Efficient resource allocation for device-to-device communication underlaying LTE Network[C]// IEEE 6th International Conference on Wireless and Mobile Computing,Networking and Communications, Octember 11-13,2010, Niagara Falls,ON,Canada. New Jersey: IEEE Press, 2010:368-375.
[6]	HYUNKEE M , JEMIN L , SUNGSOO P , et al. Capacity enhancement using an interference limited area for device-to-device uplink underlaying cellular networks[J]. IEEE Transactions on Wireless Communications, 2011,10(12): 3995-4000.
[7]	WANG H , CHU X . Distance-constrained resource-sharing criteria for device-to-device communications underlaying cellular networks[J]. Electronics Letters, 2012,48(9): 528-530.
[8]	LAN B , LI B B , LIU J , et al. Potential game resource allocation algorithm for high density D2D users[J]. Journal of South China University of Technology, 2015,43(1): 41-46,52.
[9]	YU C H , TIRKKONEN O , DOPPLER K , et al. Power optimization of device-to-device communication underlaying cellular communication[C]// IEEE International Conference on Communications, June 14-18,2009, Dresden,Germany. New Jersey: IEEE Press, 2009:1-5.
[10]	MARCO B , GABOR F , ANDREA A , et al. Performance analysis of a distributed resource allocation scheme for(D2D) communications[C]// IEEE Workshop on Machine-to-Machine Communications, December 5-9,2011, Huston,Texas,USA. New Jersey: IEEE Press, 2011:358-362.
[11]	PIRO G , GRIECO L A , BOGGIA G , et al. Simulating LTE cellular systems:an open source framework[J]. IEEE Transactions on Vehicular Technology, 2011,60(2): 498-513.
[12]	3GPP. Selection procedures for the choice of radio transmission technologies of the UMTS:TR30.03U,version3.2.0[R]. 1998.
[13]	ODUOLA W O , LI X F , QIAN L J , et al. Power control for device-to-device communications as an underlay to cellular system[C]// IEEE International Conference on Communication(ICC), June 10-14,2014, Sydney,Australia. New Jersey: IEEE Press, 2014:5257-5262.
[14]	ZHANG B , LI Y , JIN D , et al. Social-aware peer discovery for D2D communications underlaying cellular networks[J]. IEEE Transactions on Wireless Communications, 2015,14(5): 2426-2439.
[15]	YIN R , YU G D , ZHANG H Z , et al. Pricing-based interference coordination for D2D communications in cellular networks[J]. IEEE Transactions on Wireless Communications, 2015,14(3): 1519-1532.

参数	取值
小区半径/m	600
资源块数目/个	30
路径衰落模型	蜂窝模式：128.1+36.7lgd
	D2D模式：148+40lgd
阴影衰落标准差/dB	蜂窝模式： 10
	D2D模式： 12
D2D最大通信距离/m	60
用户的最大发射功率/dBm	14
蜂窝用户数/个	30
D2D链路数/个	15
接收信干比门限值/dB	-10
系统带宽/MHz	10
高斯噪声功率普密度/（dBm·Hz^-1）	-174
仿真次数/次	500
TTI/ms	200

混合D2D蜂窝网络中基于模拟退火算法的资源调度策略

Resource scheduling strategy based on simulated annealing algorithm in hybrid D2D cellular networks

在线阅读

PDF下载

可视化

摘要/Abstract

引用本文

使用本文

图/表 7

参考文献 15

相关文章 15

Metrics

推荐阅读 0

[1]	康宇, 刘雅琼, 赵彤雨, 寿国础. AI算法在车联网通信与计算中的应用综述[J]. 电信科学, 2023, 39(1): 1-19.
[2]	汪晗, 刁磊, 王梦玲, 荣欣, 李佳珉, 尤肖虎. 工业物联网中URLLC的关键问题分析[J]. 电信科学, 2022, 38(Z1): 77-92.
[3]	贺智敏, 林育哲, 程宇杰, 闫实. 基于无线感知辅助的车联网下行无线资源分配方法[J]. 电信科学, 2022, 38(9): 60-70.
[4]	王越, 许方敏, 曹海燕. TDD模式下无小区大规模MIMO系统的导频干扰抑制[J]. 电信科学, 2022, 38(5): 87-94.
[5]	邹璐珊, 黄晓雯, 杨敬民, 郑艺峰, 张光林, 张文杰. 移动边缘计算中资源分配和定价方法综述[J]. 电信科学, 2022, 38(3): 113-132.
[6]	绳韵, 许晨, 郑光远. 基于NOMA的超密集MEC网络任务卸载和资源分配方案[J]. 电信科学, 2022, 38(2): 35-46.
[7]	丁铖, 陈锦荣, 曹小冬, 王翊. 基于服务质量的层次化结构资源分配算法[J]. 电信科学, 2022, 38(1): 102-111.
[8]	翟捷萍, 刘小兰, 肖海林. 基于信道反转的C-V2X动态功率控制方案[J]. 电信科学, 2021, 37(2): 71-81.
[9]	余云河, 孙君. 机器类通信中集中式与分布式Q学习的资源分配算法研究[J]. 电信科学, 2021, 37(11): 41-50.
[10]	吴柳青,朱晓荣. 基于边-端协同的任务卸载资源分配联合优化算法[J]. 电信科学, 2020, 36(3): 42-52.
[11]	李凯,刘伟,罗贵阳,李静林. 以用户为中心的智能化网络运营服务方法[J]. 电信科学, 2020, 36(2): 101-108.
[12]	贾海宇,陈佳,王铭鑫. 无线接入网络中网络功能虚拟化研究综述[J]. 电信科学, 2019, 35(1): 97-112.
[13]	易冰,陈永丽,赵瑞雪. 毫米波5G网络中D2D通信的资源分配方案[J]. 电信科学, 2019, 35(1): 138-146.
[14]	李学华,沈琛,姚媛媛. 基于跨层策略的60 GHz脉冲多用户通信系统性能分析[J]. 电信科学, 2018, 34(9): 70-77.
[15]	葛维春,罗桓桓,周桂平,王英杰,孔祥余,关璐瑶,宋闯,张民,李青. 基于电力光纤到户的网络切片资源管理方案[J]. 电信科学, 2018, 34(9): 153-159.