摘要
提出了一种大规模机器类通信(mMTC)中基于功率控制的高可靠低迟延(URLL)上行无线资源优化方案.考虑时分双工蜂窝网络,设计了上行链路传输的反向功率控制方案,并导出了基于距离的链路可靠性函数;在此基础上,建立了上行无线资源优化模型,分析了链路可靠性函数的特性,并提出了一种基于黄金分割搜索最优的传输错误概率算法;给出了一种最小化系统所需的总带宽算法,可为每个用户分配多个子信道,用户通过判断信道增益是否超过门限值来选择子信道.仿真实验结果表明,新方案在迟延和可靠性的改进以及总带宽、功耗等方面的优势显著.
An optimal scheme of uplink resource allocation for ultra-reliable and low-latency(URLL)in massive machine type communications(m MTC)with power control is proposed.Considering time division duplexing(TDD)cellular networks,the reverse power control scheme of uplink transmission by using the distance measurement capability of multi-antenna TDD base station is designed and the linkbased reliability function based on distance is derived.Further,the optimization model of uplink radio resources is built.Then the characteristic of the link reliability function is analyzed and an optimal transmission error probability algorithm based on golden section is proposed.Furthermore,an algorithm to minimize the total bandwidth required by the system is given.Multiple sub-channels may be assigned to each user,and the user selects the sub-channel by judging whether the channel gain exceeds the threshold.Finally,simulation experiments show the improvement of latency and reliability,as well as the performance advantages of total bandwidth,power consumption and so on.
作者
谢显中
黎佳
黄倩
陈杰
XIE Xian-zhong;LI Jia;HUANG Qian;CHEN Jie(Institute of Personal Communications,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Institute of Broadband Access Networks,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)
出处
《北京邮电大学学报》
EI
CAS
CSCD
北大核心
2018年第6期45-51,共7页
Journal of Beijing University of Posts and Telecommunications
基金
国家自然科学基金项目(61271259
61471076
61601070)
重庆市教委科学技术研究项目(KJ1600411)
重庆市教委重点实验室专项项目(JK12010000062)
重庆市基础与前沿研究计划项目(CSTC 2016jcyjA0455)
长江学者和创新团队发展计划项目(IRT1299)
重庆市研究生科研创新项目(CYS17223
CYB17131)
重庆邮电大学博士高端人才项目(BYJS2017003)
关键词
大规模机器类通信
高可靠低迟延
功率控制
无线资源优化
总带宽
功耗
massive machine type communications
ultra-reliable and low-latency
power control
resource optimization
total bandwidth
power consumption
