高速铁路移动通信下基于IMT-A的时变信道建模
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摘要
信道建模及其仿真方法是高速铁路移动通信系统设计的难点,同时已有的面向高速移动下IMT-A时变信道建模的研究仍存在不足。针对上述挑战,提出了一种高铁移动下具有时变参数的基于IMT-A信道的建模方法。首先,针对IMT-A的城市宏小区场景,设计了一个马尔可夫过程来模拟时变簇的数量变化,接着推导出随时间变化的信道参数的表达式,其中包括簇的延迟、功率、离开角和到达角,并得到了信道冲激响应;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平稳间隔;最后,对所提信道模型的统计性质进行了仿真,验证了该模型具有时变性且高速铁路信道具有的非平稳性,并证明了所提信道模型可用来模拟高速铁路信道的可行性。
Channel modeling and its simulation method is a difficult point of high-speed train mobile communication system design. At the same time,there are still some researches on IMT-A time-varying channel modeling for high-speed train mobile communication. Aiming at the above challenges,this paper presented a modeling method based on IMT-A channel with highspeed train mobile with time-varying parameters. Firstly,for the urban macro-cell(UMA) scene of IMT-A,this paper designed a Markov process to simulate the number of time-varying clusters,and then derived the expression of the channel parameters with time,including the delay,power,angle and reach angle,and got the channel impulse response(CIR). Secondly,it analyzed the time-varying space-time cross-correlation function(CCF),time-varying auto-correlation function(ACF) and stationary interval of channel. Finally,it simulated the statistical properties of the proposed channel model,which proves the non-stationarity of the model and the non-stationarity of the high-speed train channel,and proves that the proposed channel model can be used to simulate the feasibility of high-speed train channel.
Channel modeling and its simulation method is a difficult point of high-speed train mobile communication system design. At the same time,there are still some researches on IMT-A time-varying channel modeling for high-speed train mobile communication. Aiming at the above challenges,this paper presented a modeling method based on IMT-A channel with highspeed train mobile with time-varying parameters. Firstly,for the urban macro-cell(UMA) scene of IMT-A,this paper designed a Markov process to simulate the number of time-varying clusters,and then derived the expression of the channel parameters with time,including the delay,power,angle and reach angle,and got the channel impulse response(CIR). Secondly,it analyzed the time-varying space-time cross-correlation function(CCF),time-varying auto-correlation function(ACF) and stationary interval of channel. Finally,it simulated the statistical properties of the proposed channel model,which proves the non-stationarity of the model and the non-stationarity of the high-speed train channel,and proves that the proposed channel model can be used to simulate the feasibility of high-speed train channel.
引文
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[2] Yang Jingya,Ai Bo,Guan Ke,et al. Quasi-stationarity regions analysis for channel in composite high-speed railway scenario[C]//Proc of IEEE International Symposium on Antennas and Propagation.Piscataway,NJ:IEEE Press,2016:1699-1700.
[3] Lin Siyu,Kong Linghe,He Liang,et al. Finite-state Markov modeling for high-speed railway fading channels[J]. IEEE Antennas&Wireless Propagation Letters,2015,14:954-957.
[4] Matolak D W. V2V communication channels:state of knowledge,new results,and what’s next[M]//Communication Technologies for Vehicles. Berlin:Springer,2013:1-21.
[5] Xuan Li,Chao Shen,Ai Bo,et al. Finite-state Markov modeling of fading channels:a field measurement in high-speed railways[C]//Proc of IEEE/CIC International Conference on Communications in China.Piscataway,NJ:IEEE Press,2013:577-582.
[6] Molisch A F,Tufvesson F. Propagation channel models for next-generation wireless communications systems[J]. IEICE Trans on Communications,2014,97(10):2022-2034.
[7] Wu Shangbin,Wang Chengxiang,Haas H,et al. A non-stationary wideband channel model for massive MIMO communication systems[J]. IEEE Trans on Wireless Communications,2015,14(3):1434-1446.
[8] Molisch A F,Karttunen A,Hur S,et al. Spatially consistent pathloss modeling for millimeter-wave channels in urban environments[C]//Proc of European Conference on Antennas and Propagation.Piscataway,NJ:IEEE Press,2016:1-5.
[9] Wu Shangbin,Wang Chengxiang,Aggoune E H M,et al. A non-stationary 3-D wideband twin-cluster model for 5G massive MIMO channels[J]. IEEE Journal on Selected Areas in Communications,2014,32(6):1207-1218.
[10]Guan Ke,Ai Bo,Fricke A,et al. Excess propagation loss modeling of semiclosed obstacles for intelligent transportation system[J]. IEEE Trans on Intelligent Transportation Systems,2016,17(8):2171-2181.