高速移动下U型槽的时变信道建模

doi:10.11772/j.issn.1001-9081.2017.10.2735

计算机应用 ›› 2017, Vol. 37 ›› Issue (10): 2735-2741.DOI: 10.11772/j.issn.1001-9081.2017.10.2735

• 网络与通信 • 下一篇

高速移动下U型槽的时变信道建模

廖勇^1,2, 胡异¹

1. 重庆大学通信与测控中心, 重庆 400044;
2. 综合业务网理论及关键技术国家重点实验室(西安电子科技大学), 西安 710071

收稿日期:2017-04-12 修回日期:2017-06-02 出版日期:2017-10-10 发布日期:2017-10-16
通讯作者: 廖勇(1982-),男,四川自贡人,副研究员,博士,CCF高级会员,主要研究方向:高速移动通信、飞行器测控与通信,E-mail:liaoy@cqu.edu.cn
作者简介:廖勇(1982-),男,四川自贡人,副研究员,博士,CCF高级会员,主要研究方向:高速移动通信、飞行器测控与通信;胡异(1994-),女,重庆人,硕士研究生,主要研究方向:高速移动通信中的信道模型及其建模方法.
基金资助:
国家自然科学基金资助项目（61501066，61571069）；重庆市基础与前沿研究计划项目（cstc2015jcyjA40003）；中央高校基本科研业务费专项资金资助项目（106112017CDJXY500001，106112017CDJQJ168817）；西安电子科技大学综合业务网理论及关键技术国家重点实验室开放基金资助项目（ISN16-03）。

High-speed mobile time-varying channel modeling under U-shaped groove

LIAO Yong^1,2, HU Yi¹

1. Center of Communication and TT&C, Chongqing University, Chongqing 400044, China;
2. State Key Laboratory of Integrated Services Networks (Xidian University), Xi'an Shaanxi 710071, China

Received:2017-04-12 Revised:2017-06-02 Online:2017-10-10 Published:2017-10-16
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61501066, 61571069), the Chongqing Frontier and Applied Basic Research Project (cstc2015jcyjA40003), the Fundamental Research Funds for the Central Universities (106112017CDJXY500001, 106112017CDJQJ168817), the Open Fund of the State Key Laboratory of Integrated Services Networks (ISN16-03).

摘要/Abstract

摘要： 随着国内高速铁路建设的迅速发展，在高速铁路上要求移动办公、娱乐的客户需求与日俱增，而现有的蜂窝移动通信以及针对铁路的移动通信铁路全球系统（GSM-R）均不能很好地满足客户对宽带无线通信的服务质量（QoS）需求。高铁在实际的行驶过程中，会经历各种复杂的场景，U型槽是常见的场景，然而目前尚未有充分针对高速移动下U型槽的时变信道建模的研究。针对此问题，提出一种高速移动下U型槽的时变信道建模方法。首先，采用几何随机分布理论，针对高铁典型场景U型槽建立几何分布模型，分析散射体簇的变化规律，推导视距（LOS）分布、时变角度扩展、时变多普勒扩展等参数的表达式，并给出了信道冲击响应的闭式解。其次，分析了信道的时变空时域互相关函数、时变自相关函数以及时变空域多普勒功率谱密度的表达式。最后，对所提模型进行了统计性能的仿真，验证了该模型具有时变性以及较高的相关性，体现了高铁信道的非平稳性，满足高速无线信道的特性。

关键词: 高速移动, 信道模型, U型槽, 时变信道, 几何随机分布

Abstract: With the rapid development of the domestic high-speed railway construction, customer demand for mobile office and entertainment on high-speed railway is growing rapidly. While both of the existing cellular mobile communication and proprietary communication network for Global System for Mobile communication-Railway (GSM-R) cannot satisfy customer demand for Quality of Service (QoS) of broadband wireless communication. High-speed railway will experience all kinds of complex scenarios during the actual driving, and U-shaped groove scene is a common one. However, there is not a full research on time-varying channel modeling of the U-shaped groove scenario under high-speed mobile environment. Therefore, a U-shaped groove time-varying channel modeling method under high-speed mobile environment was proposed and simulated. Firstly, the geometric random distribution theory was used to established geometric distribution model for high-speed railway scenario under U-shaped groove, and the change law of scatterers was analyzed. Besides, the parameters' closed mathematical expressions such as line-of-sight distribution, time-varying angle spread, time-varying Doppler spread were deduced, and the closed solution of the channel impulse response was given. Secondly, the time-variant space-time cross-correlation function, time-variant auto-correlation function and time-variant space-Doppler power spectrum density were analyzed. Finally, the simulations of statistical performance were carried out to verify the proposed model. The simulation results show that the proposed model has the properties of time-varying and high correlation, which verifies the non-stationary of high-speed wireless channel and satisfies the characteristics of high-speed wireless channel.

Key words: high-speed mobility, channel model, U-shaped groove, time-varying channel, geometric random distribution

中图分类号:

TN929.5

廖勇, 胡异. 高速移动下U型槽的时变信道建模[J]. 计算机应用, 2017, 37(10): 2735-2741.

LIAO Yong, HU Yi. High-speed mobile time-varying channel modeling under U-shaped groove[J]. Journal of Computer Applications, 2017, 37(10): 2735-2741.

参考文献

[1] GOLLER M. Application of GSM in high speed trains: measurements and simulations[C]//Proceedings of the 1995 IEE Colloquium on Radiocommunications in Transportation. Piscataway, NJ: IEEE, 1995: 1-7.
[2] BRISO C, CORTES C, ARQUES F J, et al. Requirements of GSM technology for the control of high speed trains[C]//Proceedings of the 13th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications. Piscataway, NJ: IEEE, 2002: 792-793.
[3] GUAN K, ZHONG Z, AI B. Assessment of LTE-R using high speed railway channel model[C]//Proceedings of the 2011 Third International Conference on Communications and Mobile Computing. Piscataway, NJ: IEEE, 2011: 461-464.
[4] KASTELL K, BUG S, NAZAROV A, et al. Improvements in railway communication via GSM-R[C]//Proceedings of the IEEE 63rd Vehicular Technology Conference. Piscataway, NJ: IEEE, 2006: 3026-3030.
[5] KNORZER S, BALDAUF M A, FUGEN T, et al. Channel analysis for an OFDM-MISO train communications system using different antennas[C]//Proceedings of the 2007 IEEE 66th Vehicular Technology Conference. Piscataway, NJ: IEEE, 2007: 809-813.
[6] GUAN K, ZHONG Z, AI B, KURNER T. Deterministic propagation modeling for the realistic high-speed railway environment[C]//Proceedings of the 2013 IEEE 77th Vehicular Technology Conference. Piscataway, NJ: IEEE, 2013: 1-5.
[7] CICHON D J, BECKER T C, WIESBECK W. Determination of time-variant radio links in high-speed train tunnels by ray optical modeling[C]//Proceedings of the 1995 Antennas and Propagation Society International Symposium. Piscataway, NJ: IEEE, 1995, 1: 508-511.
[8] CICHON D J, ZWICK T, WIESBECK W. Ray optical modeling of wireless communications in high-speed railway tunnels[C]//Proceedings of the IEEE 46th Vehicular Technology Conference, Mobile Technology for the Human Race. Piscataway, NJ: IEEE, 1996, 1: 546-550.
[9] ZHENG Q, XU C, WU M. A novel MIMO channel model for high speed railway system[C]//Proceedings of the IEEE 14th International Conference on Communication Technology. Piscataway, NJ: IEEE, 2012: 31-35.
[10] GHAZAL A, WANG C, HAAS H, et al. A non-stationary MIMO channel model for high speed train communication systems[C]//Proceedings of the IEEE 75th Vehicular Technology Conference. Piscataway, NJ: IEEE, 2012: 1-5.
[11] GHAZAL A, WANG C, HAAS H, et al. A non-stationary geometry-based stochastic model for MIMO high-speed train channels[C]//Proceedings of the IEEE 12th International Conference on ITS Telecommunications. Piscataway, NJ: IEEE, 2012: 7-11.
[12] GHAZAL A, WANG C, AI B, et al. A nonstationary wideband MIMO channel model for high-mobility intelligent transportation systems [J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(2): 885-897.
[13] CHEN B, ZHONG Z. Geometry-based stochastic modeling for MIMO channel in high-speed mobile scenario[J]. International Journal of Antennas & Propagation, 2012,2012: Article ID 184682.
[14] LIN S, ZHONG Z, CAI L, et al. Finite state Markov modelling for high speed railway wireless communication channel[C]//Proceedings of the 2012 IEEE Global Communications Conference. Piscataway, NJ: IEEE, 2012: 5421-5426.
[15] XUAN L, CHAO S, AI B, et al. Finite-state Markov modeling of fading channels: a field measurement in high-speed railways[C]//Proceedings of the 2013 IEEE/CIC International Conference on Communications in China. Piscataway, NJ: IEEE, 2013: 577-582.
[16] AI B, HE R, ZHONG Z, et al. Radio wave propagation scene partitioning for high-speed rails[J]. International Journal of Antennas & Propagation, 2012(2012), Article ID 815232.
[17] 邱佳慧, 陶成, 刘留, 等. U型槽无线信道多径传播特性测量与建模方法的研究[J]. 铁道学报, 2014, 36(1): 40-48. (QIU J H, TAO C, LIU L, et al. Research on measurement and modeling of wireless channel multipath propagation properties for U-shape cutting[J]. Journal of the China Railway Society, 2014, 36(1): 40-48.)

高速移动下U型槽的时变信道建模

High-speed mobile time-varying channel modeling under U-shaped groove

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 6

编辑推荐

Metrics

[1]	景兴红, 孙国栋, 何世彪, 廖勇. 基于滑窗滤波和多项式拟合的时变信道估计方法[J]. 计算机应用, 2021, 41(9): 2699-2704.
[2]	王思秀, 张蕾, 任艳, 冯长征. 基于自相关增量的载波参数解耦合技术[J]. 计算机应用, 2019, 39(11): 3339-3342.
[3]	郭业才, 赵卫娟, 张秀再. 卫星信道三状态Markov模型设计与仿真[J]. 计算机应用, 2016, 36(1): 91-95.
[4]	覃彩玲, 肖琨. 基于信道预测的协作中继选择方法[J]. 计算机应用, 2015, 35(9): 2419-2423.
[5]	潘成胜李花芳刘春玲. Ka频段移动卫星星地链路误码统计分析[J]. 计算机应用, 2012, 32(08): 2137-2140.
[6]	师小琳. 瑞利衰落信道改进模型及性能分析[J]. 计算机应用, 2011, 31(08): 2059-2061.