3-D非平稳宽带MIMO信道模型：考虑移动站速度变化的影响

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"这篇研究论文提出了一种3-D非平稳宽带MIMO信道模型，该模型考虑了移动站（MS）速度变化的情况。通常，现有的信道模型假设MS以恒定速度直线移动，但实际环境中的MS运动可能更为复杂。论文采用WINNER +通道模型的数据来增强模拟的真实感，对包括空间互相关函数（CCF）、时间自相关函数（ACF）和多普勒功率谱密度（PSD）在内的统计特性进行了推导和分析。研究发现，MS速度变化显著影响信道模型的统计特性，并且提出的模型可以作为未来非平稳信道建模的基础框架。" 本文的核心内容围绕着改进现有的MIMO信道模型展开。传统的信道模型往往忽视了移动设备在实际运动中速度和轨迹的变化，而这些变化在现代无线通信系统中具有重要的影响。作者们引入了3-D非平稳的特性，这意味着模型不仅考虑了空间维度，还考虑了随时间变化的动态因素，如MS速度的变化。为了提高模型的准确性，研究者采用了WINNER +通道模型的数据。WINNER +是国际上广泛认可的无线信道模型，它提供了丰富的环境和移动条件下的信道特征，使得新模型在仿真时更接近实际环境。在分析部分，论文重点研究了几个关键的信道统计特性。空间互相关函数（CCF）描述了不同天线之间的信号相关性，这对于多天线系统中的信号处理至关重要。时间自相关函数（ACF）则反映了信号强度随时间的变化，这对于理解多普勒频移的影响非常关键。此外，多普勒功率谱密度（PSD）分析揭示了由于MS速度变化产生的频率漂移，这对设计高速移动环境下的同步和均衡算法具有指导意义。研究表明，MS速度的变化显著影响了这些统计特性的行为，这在设计和优化无线通信系统时必须考虑。因此，提出的3-D非平稳宽带MIMO信道模型提供了一个更全面的框架，能够更好地反映真实世界中移动通信的复杂性。这一模型有望对未来的无线通信标准和系统设计提供有力的支持，尤其是在高速移动场景下，对于改善传输效率和可靠性具有重要意义。

A 3-D Non-Stationary Wideband MIMO Channel

Model Allowing for Velocity Variations of the

Mobile Station

Ji Bian

, Cheng-Xiang Wang

, Minggao Zhang

, Xiaohu Ge

, and Xiqi Gao

Shandong Provincial Key Lab of Wireless Communication Technologies, Shandong University, Jinan, 250100, China.

Institute of Sensors, Signals and Systems, School of Engineering & Physical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, UK.

Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.

School of Information Science and Engineering, Southeast University, Nanjing, 210096, China.

Email: bianjimail@163.com, cheng-xiang.wang@hw.ac.uk, zmg225@163.com, xhge@mail.hust.edu.cn, xqgao@seu.edu.cn

Abstract—Most channel models in the literature are based

on the assumption that the mobile station (MS) moves along

a straight line with a constant speed. In a realistic environment,

the MS may experience changes in their speeds and trajectories.

In this paper, a three-dimensional (3-D) non-stationary wideband

multiple-input multiple-output (MIMO) channel model allowing

for velocity variations of the MS is proposed. The parameters

are obtained from the WINNER+ channel model to make the

simulations more realistic. Statistical properties including spatial

cross-correlation function (CCF), temporal autocorrelation func-

tion (ACF), and Doppler power spectral density (PSD) are derived

and analyzed. Our ﬁndings show that a variation of the velocity

of the MS has a signiﬁcant impact on the statistical properties of

the channel model. Furthermore, the proposed channel model can

be used as a basic framework for future non-stationary channel

modeling.

Index Terms—Non-stationary, GBSM, statistical properties,

trajectory variations, time-variant parameters.

I. INTRODUCTION

The development of the ﬁfth generation (5G) wireless

communication systems is being carried out in full swing [1]–

[4]. The mobility features of the 5G wireless communication

networks call for the need for accurate and effective channel

models which are able to capture the dynamic properties

of the real wireless propagation environments. A common

assumption in channel modeling is that the channel fulﬁlls

the wide-sense stationary (WSS) condition. However, the

WSS assumption is only valid when the observation time

interval is much shorter than the stationary interval. Channel

models with WSS assumption may neglect the non-stationary

characteristics of the channel, especially in high mobility

scenarios [5]–[7]. In realistic propagation scenarios, the non-

stationarity of the channel could be a result of movements of

scatterers such as fallen leaves, pedestrians, and vehicles. In

[8], a non-stationary 3-D wideband twin-cluster channel model

was proposed. The clusters are in motion or stay static with

certain probabilities and a birth-death process was adopted to

model the clusters’ appearance and disappearance. Another

major cause leading to wireless channels’ non-stationarity is

the movement of MS. The COST family channel models, e.g.,

the COST 2100 channel model [9] introduced the concept of

visibility region (VR). As the MS enters and leaves different

VRs, the active clusters that can be seen by the MS change,

resulting in a non-stationary channel.

Most channel models in the literature [10]–[13] are based

on the assumption that the MS moves with a constant speed

in a ﬁxed direction. However, in a realistic environment, the

MS may experience acceleration/deceleration caused by trafﬁc

lights and change the movement direction when cornering,

which can cause a signiﬁcant impact on the statistics of

wireless channels. However, the channel models allowing for

velocity variations of the MS are still very limited. The authors

in [14] analyzed the statistics of the channel when the MS

moves with a constant acceleration but in a ﬁx direction.

The authors in [15] proposed a two-dimensional (2-D) non-

stationary channel model allowing the MS to move with

varying velocity (both speeds and directions). In [16], the

authors expanded the work of [15] into a mobile-to-mobile

(M2M) channel model, in which both the transmitter and the

receiver can change their velocities over time. The temporal

ACF and the Wigner spectrum of the proposed model were

derived. The authors in [17] proposed a 2-D non-stationary

channel model using a sum-of-chirps (SOC

) process and

the Doppler PSD was analyzed through the Wigner spectrum.

However, channel models in [15]–[17] are 2-D channel models

and ignored the time evolution of clusters. Besides, the channel

models in [15] and [16] can only model isotropic scattering

environment.

In this paper, a 3-D non-stationary wideband MIMO channel

model is proposed. The MS of the proposed channel model

is allowed to move with an acceleration and move in curves,

e.g., a sine shaped trajectory. The spatial CCF, temporal ACF,

and Doppler PSD of the proposed channel model are derived

and analyzed. It is shown that the motion of the MS has a

signiﬁcant impact on the statistical properties of the channel

model. Furthermore, the channel model can be adapted to

various scenarios by setting different channel parameters.

The remainder of this paper is organized as follows. In

Section II, a 3-D non-stationary wideband MIMO channel

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