超密集场景下考虑业务动态的功率匹配算法

doi:10.13190/j.jbupt.2019-002

北京邮电大学学报 ›› 2019, Vol. 42 ›› Issue (5): 48-53.doi: 10.13190/j.jbupt.2019-002

超密集场景下考虑业务动态的功率匹配算法

张晖^1,2,3, 刘姝¹, 赵海涛¹, 孙雁飞²

1. 南京邮电大学江苏省无线通信重点实验室, 南京 210003;
2. 南京邮电大学通信与网络技术国家工程研究中心, 南京 210003;
3. 苏州大学江苏省计算机信息处理技术重点实验室, 江苏苏州 215006

收稿日期:2019-02-22 出版日期:2019-10-28 发布日期:2019-11-25
作者简介:张晖(1982-),男,教授,硕士生导师,E-mail:zhhjoice@126.com.
基金资助:
国家自然科学基金项目（61471203，61772286）；江苏省"六大人才高峰"项目（RJFW-024）；江苏省"青蓝工程"项目（2016）；南京邮电大学"1311"人才计划项目（2015）；通信与网络技术国家工程研究中心开放课题（TXKY17002）；江苏省计算机信息处理技术重点实验室开放课题（KJS1518）；国家科技重大专项项目（2012ZX03001008-003）

Power Matching Algorithm Considering Service Dynamics in Ultra-Dense Scenarios

ZHANG Hui^1,2,3, LIU Shu¹, ZHAO Hai-tao¹, SUN Yan-fei²

1. Jiangsu Key Laboratory of Wireless Communications, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
2. National Engineering Research Center of Communications and Networking, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
3. Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Jiangsu Suzhou 215006, China

Received:2019-02-22 Online:2019-10-28 Published:2019-11-25

摘要/Abstract

摘要： 提出了一种面向超密集场景的考虑业务动态的无线网络功率资源匹配算法.首先，根据网络异构和业务动态变化特征，建立双层动态博弈模型.针对不同博弈层参与者的需求特性，以最大化效用函数为准则，设计不同的效益模型，并通过对网络中业务动态性的预测调整定价因子，以更准确地反映网络环境的变化；其次，根据双层非合作博弈的特性进行分层功率博弈求解，通过宏蜂窝用户与微基站以及微蜂窝用户之间的多次非合作功率博弈达到均衡；最后，通过与现有功率资源匹配算法仿真比较，所提算法具有优越的性能.

关键词: 热点高容量场景, 双层动态博弈, 业务预测, 资源匹配

Abstract: A wireless network resource matching algorithm considering service dynamics in ultra-dense scenarios is proposed. Firstly, according to heterogeneous characteristics of networks and dynamic changes of services, a two-layer dynamic game model was established. In particular, different benefit models were designed to maximize the utility function based on the demand characteristics of different game layer participants, and a pricing factor was dynamically adjusted by predicting service dynamics more accurately to reflect the network environment. Secondly, according to the characteristics of the two-tier non-cooperative game model, a layered power game was solved, so that an equilibrium was achieved through multiple non-cooperative power games among macro cell users, micro base stations and micro cell users. Finally, compared with several existing resource matching algorithms, the simulation results of our algorithm showed superior performances.

Key words: hot-spot high-capacity scenario, two-layer dynamic game, service forecast, resource matching

中图分类号:

TP181

张晖, 刘姝, 赵海涛, 孙雁飞. 超密集场景下考虑业务动态的功率匹配算法[J]. 北京邮电大学学报, 2019, 42(5): 48-53.

ZHANG Hui, LIU Shu, ZHAO Hai-tao, SUN Yan-fei. Power Matching Algorithm Considering Service Dynamics in Ultra-Dense Scenarios[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2019, 42(5): 48-53.

参考文献

[1] 温向明, 潘奇路, 兆铭景, 等. 面向5G大连接场景的eMTC技术解析[J]. 北京邮电大学学报, 2018, 41(5):13-19. Wen Xiangming, Pan Jilu, Zhao Mingjing, et al. Analysis of eMTC for 5G mMTC scenarios[J]. Journal of Beijing University of Posts and Telecommunications, 2018, 41(5):13-19.
[2] Chen S, Qin F, Hu B, et al. User-centric ultra-dense networks for 5G:challenges, methodologies, and directions[J]. IEEE Wireless Communications, 2018, 23(2):78-85.
[3] 张海波, 李虎, 陈善学, 等. 超密集网络中混合接入方式下基于分组的资源分配[J]. 北京邮电大学学报, 2018, 41(3):69-74. Zhang Haibo, Li Hu, Chen Shanxue, et al. A cluster-based resource allocation under hybrid access mode in ultra-dense network[J]. Journal of Beijing University of Posts and Telecommunications, 2018, 41(3):69-74.
[4] Chang Y J, Kim M. Binocular suppression-based stereoscopic video coding by joint rate control with KKT conditions for a hybrid video codec system[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2015, 25(1):99-111.
[5] Tseng H W, Yu Y J, Wu B S, et al. A resource allocation sheme for device-to-device communication over ultra-dense 5G cellular networks[C]//International Conference on Applied System Innovation (ICASI). New York:IEEE Press, 2017:80-83.
[6] Zhang H, Liu S. Energy efficient resource matching algorithm for multi-homing services in dynamic wireless environment[J]. Wireless Networks, 2018(10):1-16.
[7] Zhao K, Zhang S, Zhang N, et al. Incentive mechanism for cached-enabled small cell sharing:a Stackelberg game approach[C]//IEEE Global Communications Conference (GLOBECOM). New York:IEEE Press, 2017:1-6.
[8] Roger B M. Game theory[M]. Cambridge:Harvard University Press, 2013.
[9] Ismail M, Abdrabou A, Zhuang W H. Cooperative decentralized resource allocation in heterogeneous wireless access medium[J]. IEEE Transactions on Wireless Communications, 2013, 12(2):714-724.

超密集场景下考虑业务动态的功率匹配算法

Power Matching Algorithm Considering Service Dynamics in Ultra-Dense Scenarios

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