工业物联网中基于球面波的波束域信道建模

随着天线阵列的增大,传统MIMO信道中的广义平稳(Wide-Sense Stationary, WSS)假设已失效,在大规模MIMO信道中,近场效应和非平稳性越发明显。针对波束域信道建模(Beam Domain Channel Model, BDCM)中尚未考虑到的大规模MIMO特性,将几何随机建模(Geometry-Based Stochastic Model, GBSM)中的天线域转换到波束域,提出了一个引入球面波假设的波束域信道模型。基于提出的模型,推导了时空相关函数(Spatial-Temporal Correlation Function, ST-CF),并研究了球面波假设对时空相关性的影响。通过波束扩展参数的模拟仿真表明,球面波假设下波束域信道模型具有良好的准确性。     

一种通用宽带MIMO信道模型

针对宽带的MIMO信道建模问题,提出一种通用多天线信道模型及其构造方法.该方法把克罗内克积应用到频域,同时提出频域散射衰落加权因子的概念,由此导出一种室外宽带MIMO散射分布模型.经过简化,该模型还可以应用到室内场景.仿真结果表明,这种通用信道模型能够准确的描述出宽带MIMO信道的视距(LoS)、非视距(NLoS)、室内外散射特征以及孔径效应.     

超大规模MIMO信道测量建模研究综述

超大规模多天线技术(Extra-large Scale Massive Multiple-Input Multiple-Output,XL-MIMO),是5G大规模MIMO进一步向更高空间维度的扩展和延伸。随天线数目大幅增加,XL-MIMO部署呈现超大孔径阵列等新形态;其传播信道在5G大规模MIMO信道模型近场传播、空间非平稳等特性基础上,进一步呈现出用户可视区域不同等新特点,因此,需要新的模型架构对其进行描述。基于此,对文献中XL-MIMO相关的信道测量、特征分析与建模方法进行综述。从传统无线信道模型出发,对有限维MIMO、大规模MIMO、XL-MIMO共同的信道建模理论与手段、随阵列尺寸增加所表现出的信道新特性以及新特性所催生的新模型架构进行了详细阐述,对XL-MIMO信道特性下出现的挑战与机遇进行了展望,以期为未来超大规模MIMO传输设计提供重要参考。     

新型动态簇非平稳MIMO信道模型与信道特性分析

针对传统移动-移动场景未能考虑阵列域和时间域双重非平稳特性,且不能模拟移动发射机和移动接收机间动态簇链路信道状态的问题,提出了一种新型三维动态簇非平稳多输入多输出(Multiple-Input Multiple-Output,MIMO)信道模型.该模型结合了天线阵列切换和收发端移动过程中信道非平稳特性,且利用生灭过程对非视距分量进行模拟.并针对径时延、径功率、径到达离开角等参数,对时空演进算法进行了改进.在小尺度角度参数谱服从Von Mise Fisher(VMF)分布情况的基础上,对时间和空间相关函数进行了推导.仿真结果表明,理论值与仿真值具有很好的拟合度,表明所提出的信道模型可以作为动态簇三维非平稳MIMO信道建模的设计方案.     

基于几何的高速铁路协作MIMO信道建模

协作MIMO技术通过协作发射或协作接收的方式可以将干扰信号转变为有用信号,在高铁无线通信中引入该技术,能解决回波信道响应和提高系统容量。为了掌握协作MIMO技术在高铁场景中的信道特性,该文基于几何随机散射理论,提出一个高速铁路协作MIMO信道模型,简单调整该模型中的几个关键参数即可适用于高速铁路的多种场景。基于该模型计算信道冲激响应,推导多链路空间相关函数,进行数值计算、仿真分析和实测数据验证。仿真结果显示,直射分量越强,散射分量的角度扩展越小,多链路的空间相关性越强。散射次数越少,散射分量空间相关性越强。使用北京-天津高铁段LTE专网的实测数据验证理论模型的正确性。这些结论有助于认知协作MIMO信道和进行有效的测量活动。     

MIMO无线通信系统的信道建模

MIMO信道的空时特性是决定空时信号处理的关键,一个体现信道衰落特性的MIMO信道模型对MIMO技术的研究和应用是至关重要的。本文回顾了MIMO信道建模的发展,阐述了几个典型的信道模型,指出其适用范围,给出了几个需进一步考虑的关键特性。     

蒸发波导超视距信道建模及容量估计

为衡量海上蒸发波导环境下的超视距通信系统性能,提出了一种超视距信道建模方法及容量估计方案. 基于蒸发波导折射率模型和抛物方程（parabolic equation, PE）模型研究电波沿海面蒸发波导信道传播的大尺度衰落特性,结合统计性模型研究其小尺度衰落特性,形成基于电磁仿真和统计规律的混合蒸发波导信道模型,并由此推导出系统信道容量的估算方案. 对实际海面传播环境进行电磁建模,计算了蒸发波导环境中的路径损耗分布和多天线系统的信道容量,量化了使用多输入多输出（multiple-input multiple-output, MIMO）技术带来的超视距传播性能提升. 仿真结果表明,在蒸发波导环境中采用MIMO技术能够有效地提升信道容量,实现较好的超视距传播效果. 本文结果对海上超视距通信系统的应用及性能评估具有重要意义.     

一种新的MIMO信道模型

实际无线通信环境中发送天线之间以及接收天线之间存在相关性.针对以上特点,从多径MIMO信道的特性出发,首先建立发射天线相关系数矩阵和接收天线相关系数矩阵,并将它们引入无线信道的莱斯MIMO信道模型中.最后通过分析LOS MIMO信道相关模型和瑞利衰落MIMO信道相关模型,给出了具体的建模步骤.仿真结果表明采用本文方法产生的信道模型的MIMO系统误码率更低,从而验证了该信道模型能够较好地模拟MIMO系统的空间信道.     

基于天线互耦影响的大规模MIMO TDD系统信道互易性校准算法

射频器件的非理想性和信道的时变特性影响大规模多输入多输出（multiple-input multiple-output，MIMO）系统时分双工（time division duplex，TDD）模式的信道互易性，天线阵列的耦合效应影响信道矩阵的相关性.文中提出一种基于互耦影响的大规模MIMO互易性联合校准算法，将天线之间的互耦效应引入信道矩阵，采用OTA（over-the-air）校准算法和基于自回归（auto-regression，AR）模型预测信道矩阵相结合的方案实现同时校准射频非理想性和信道时变特性引起的互易性损失.仿真结果表明，该算法能够提高系统容量，降低误码率，有效地补偿互易性损失.本文算法可以为大规模MIMO系统的多因素联合校准提供参考.     

5G工业物联网无线信道建模研究

5G移动通信时代下工业4.0正从万物互联向万物智能演进，工业物联网(Industrial Internet of Things, IIoT)是5G通信系统重要应用场景之一。为促进5G时代下工业4.0的发展，针对IIoT场景提出了一种新的基于几何的随机模型(Geometry-Based Stochastic Model, GBSM)。鉴于5G IIoT具有富散射、多移动性和毫米波等信道特性，所提模型基于正弦和(Sum of Sinusoids, SOS)理论探索毫米波IIoT信道的频率一致性。此外，该模型还基于簇的生灭过程描述了5G IIoT信道的时间-空间非平稳特性。仿真表明角度和时延等小尺度参数在频域上是平滑变化的，且均方根(Root Mean Square, RMS)延迟扩展(Delay Spread, DS)的模拟数据和射线追踪(Ray Tracing, RT)仿真数据的拟合结果较好。以上结果验证了所提模型的准确性和有效性，为5G IIoT信道特性分析、系统设计和优化提供了重要理论支撑。     

基于射线跟踪法的73 GHz走廊环境MIMO信道特性研究

为了研究5G室内走廊环境的毫米波传输特性,通过射线跟踪仿真方法预测了室内走廊环境下73 GHz毫米波MIMO信道特性。介绍了实验的仿真环境和射线跟踪仿真预测的实验方法和具体参数设置。研究了室内走廊环境下73 GHz毫米波MIMO信道的路径损耗、RMS时延扩展和MIMO信道容量变化。发现了路径损耗斜率和RMS时延数值较小。研究MIMO容量随距离变化时发现,收发机沿走廊纵向方向中间处会产生容量峰值,主要是由于该处散射丰富,NLOS分量大。研究MIMO容量特性发现增大天线间距和增大天线阵列规模可以提升容量,但是采用4×64 Massive MIMO相对于采用4×4 MIMO时容量提升较为有限。实验证实了73 GHz毫米波MIMO可以用于室内走廊环境。     

A physical scattering model for MIMO macrocellular broadband wireless channels

This paper presents a physical scattering model that predicts multiple-input multiple-output (MIMO) channel characteristics conforming well to experimental observations in macrocells. Our approach is to start with a given single-input single-output power-delay profile (defined for specific range, bandwidth and antenna parameters) and fit a scattering model that characterizes the MIMO channel. From the derived scattering model and antenna array configurations, the MIMO channel is computed using a ray-based method. Simulations of several MIMO channels are shown to exhibit experimentally observed channel correlations, antenna beamwidth effect, range dependency, and frequency selectivity.     

A Stochastic Model of the Time-Variant MIMO Channel Based on Experimental Observations

This paper proposes a stochastic multipath model that is useful for generating multiple-input–multiple-output (MIMO) channel matrices in time-variant environments. The multipath model is developed by first extracting the relevant multipath cluster characteristics from measured indoor channel data and subsequently capturing these characteristics in an autoregressive stochastic model. This model is then used to generate channel matrices whose space–time characteristics closely match those of realistic scenarios, particularly when birth and death of multipath clusters are included in the stochastic representation. Computational examples reveal the applicability and the accuracy of the approach. While the current implementation is based on data taken assuming that propagation is confined to the horizontal plane, this paper also discusses the extension of the model to describe 3-D propagation, enabling its application to a wide range of physical scenarios and antenna characteristics.      

三维MIMO信道物理模型的统计特征

提出以散射矩阵来概括并简化电波传播过程中散射体对电磁波的影响,并对传统的距离分集和极化分集多入多出（MIMO）信道模型进行扩展,建立了一种可以应用于各种分集情况的三维通用MIMO物理信道模型。再以此模型为基础,对三维环境中的MIMO信道统计特征进行了研究,推导出任意情况下交叉极化鉴别度（XPD）和子信道间相关性的计算方法,并进行了仿真验证。仿真结果表明从文中所提出信道模型提取得到的统计特征与理论分析的结果是相符的。     

Spatially and temporally correlated MIMO channels: modeling and capacity analysis

Wireless communication systems employing multiple antennas at both the transmitter and receiver have been shown to offer significant gains over single-antenna systems. Recent studies on the capacity of multiple-input-multiple-output (MIMO) channels have focused on the effect of spatial correlation. The joint effect of spatial and temporal correlation has not been well studied. In this paper, a geometric MIMO channel model is presented, which considers motion of the receiver and nonisotropic scattering at both ends of the radio link. A joint space-time cross-correlation function is derived from this model and variates with this joint correlation are generated by using the vector autoregressive stochastic model. The outage capacity of this channel is considered where the effects of antenna spacing, antenna array angle, degree of nonisotropic scattering, and receiver motion are investigated. When n transmit and n receive antennas are employed, it is shown that the outage capacity still increases linearly with respect to n, despite the presence of spatial and temporal correlation. Furthermore, analytical expressions are derived for the ergodic capacity of a MIMO channel for the cases of spatial correlation at one end and at both ends of the radio link. The latter case does not lend itself to numerical evaluation, but the former case is shown to be accurate by comparison with simulation results. The proposed analysis is very general, as it is based on the transmit and receive antenna correlations matrices.     

Energy efficiency of massive MIMO wireless communication systems with antenna selection

Massive multiple-input multiple-output (MIMO) requires a large number (tens or hundreds) of base station antennas serving for much smaller number of terminals, with large gains in energy efficiency and spectral efficiency compared with traditional MIMO technology. Large scale antennas mean large scale radio frequency (RF) chains. Considering the plenty of power consumption and high cost of RF chains, antenna selection is necessary for Massive MIMO wireless communication systems in both transmitting end and receiving end. An energy efficient antenna selection algorithm based on convex optimization was proposed for Massive MIMO wireless communication systems. On the condition that the channel capacity of the cell is larger than a certain threshold, the number of transmit antenna, the subset of transmit antenna and servable mobile terminals (MTs) were jointly optimized to maximize energy efficiency. The joint optimization problem was proved in detail. The proposed algorithm is verified by analysis and numerical simulations. Good performance gain of energy efficiency is obtained comparing with no antenna selection.     

动态MIMO散射无线信道模型及性能分析

基于多入多出(MIMO)散射无线信道模型,提出一种动态MIMO散射无线信道模型,分析散射体及其收发多天线的运动对MIMO无线信道空域相关性及其容量的影响,得出这种影响是由收发天线的初始位置、运动速度及其传播环境决定的.数值模拟验证了这种影响,并指出空域相关性随天线单元间距增大而减小,随散射信号角度扩展增大不是一致减小,存在使相关性达最小的角度扩展值.     

基于建筑模型的5G Massive MIMO天馈寻优方法研究与应用

当前5G MR/MDT等定位技术尚不成熟且样本过少,本文提出了一种基于建筑物信息的5G Massive MIMO天馈寻优方法,利用5G大规模阵列天线的技术优势,通过Massive MIMO天线波瓣宽度的精确计算,实现了天线覆盖方案的寻优,以最大程度地提升室内覆盖.本方法在降低网络运维成本的同时,提升了资源效能,为后续5...