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1. 北京科技大学计算机与通信工程学院,北京 100083
2. 北京信息科技大学信息与通信工程学院,北京 100083
[ "戴晓明(1973- ),男,博士,北京科技大学教授、博士生导师,主要研究方向为宽带无线通信、5G+/6G、人工智能、NOMA 及大数据处理等" ]
[ "庞立卓(2000- ),女,北京科技大学硕士生,主要研究方向为大规模多输入多输出系统、随机接入" ]
[ "常争(2001- ),男,北京科技大学硕士生,主要研究方向为非正交多址接入" ]
[ "张馨月(1999- ),女,北京科技大学硕士生,主要研究方向为随机接入、非正交多址接入" ]
[ "邢怡然(1999- ),女,北京科技大学硕士生,主要研究方向为大规模多输入多输出系统、信号检测与估计" ]
[ "王曦元(1981- ),男,博士,北京信息科技大学副教授,主要研究方向为无线通信、信息论和信号处理" ]
网络出版日期:2022-10,
纸质出版日期:2022-10-20
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戴晓明, 庞立卓, 常争, 等. 面向mMIMO系统的模式分割随机接入方案[J]. 电信科学, 2022,38(10):57-66.
Xiaoming DAI, Lizhuo PANG, Zheng CHANG, et al. Pattern division random access (PDRA) scheme for mMIMO systems[J]. Telecommunications science, 2022, 38(10): 57-66.
戴晓明, 庞立卓, 常争, 等. 面向mMIMO系统的模式分割随机接入方案[J]. 电信科学, 2022,38(10):57-66. DOI: 10.11959/j.issn.1000-0801.2022277.
Xiaoming DAI, Lizhuo PANG, Zheng CHANG, et al. Pattern division random access (PDRA) scheme for mMIMO systems[J]. Telecommunications science, 2022, 38(10): 57-66. DOI: 10.11959/j.issn.1000-0801.2022277.
为提升海量机器类通信(massive machine-type communication,mMTC)设备的随机接入(random access, RA)性能,提出一种面向大规模多输入多输出(massive multiple-input multiple-output,mMIMO)系统的模式分割随机接入(pattern division random access,PDRA)方案。该方案将导频竞争空间扩展到模式域,通过叠加同一ZC(Zadoff-Chu)根序列的L个不同循环移位序列,设计基于“图样叠加”的模式域导频,在不增加物理资源的前提下扩大导频集合。仿真结果表明,在不影响信道估计和数据检测性能的前提下,与传统 RA方案相比,PDRA方案能够显著降低导频碰撞概率,提高接入成功率。
To enhance the massive machine-type communications (mMTC) random access (RA) performance
a pattern division random access (PDRA) scheme was proposed for massive multiple-input multiple-output (mMIMO) systems.In this scheme
the pilot contention space was expanded to the pattern-domain.To enlarge the size of contention space without resorting to increasing the physical resources
the pattern-domain pilot was constructed based on the superposition of L cyclically-shifted Zadoff-Chu (ZC) sequences.Simulation results illustrate that the PDRA scheme can reduce pilot collision probability significantly
and improve the access success probability compared with the conventional RA scheme
without compromising excessively on channel estimation and data detection performance.
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