A 3-D Non-Stationary Wideband MIMO Channel
Model Allowing for Velocity Variations of the
Mobile Station
Ji Bian
1
, Cheng-Xiang Wang
2
, Minggao Zhang
1
, Xiaohu Ge
3
, and Xiqi Gao
4
1
Shandong Provincial Key Lab of Wireless Communication Technologies, Shandong University, Jinan, 250100, China.
2
Institute of Sensors, Signals and Systems, School of Engineering & Physical Sciences, Heriot-Watt University, Edinburgh, EH14 4AS, UK.
3
Department of Electronics and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.
4
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
h
) 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
资源评论
weixin_38640473
- 粉丝: 8
- 资源: 949
最新资源
- 51单片机485全双工通信protues仿真C语言.zip
- 51单片机1602字符液晶滚动演示程序protues仿真.zip
- 51单片机1602液晶显示的DS1302实时时钟protues仿真C语言.zip
- 由信安之路团队成员收集整理的与渗透测试相关的 Github 项目地址，如果你由更好的项目请将项目地址发送到myh0st@foxmail.com.zip
- 51单片机1602+ds12b80+ds1302+音乐+电子书+流水灯的多功能电子表protues仿真.zip
- 51单片机BCD译码数码管显示数字protues仿真.zip
- 51单片机AT24C02的多机通信protues仿真C语言.zip
- 51单片机12864LCD图形滚动演示protues仿真C语言.zip
- 51单片机DS18B20温度传感器protues仿真.zip
- 51单片机DS1302的日历时钟protues仿真.zip
- 51单片机DS1302时钟+DS18B20+无线遥控应用程序protues仿真.zip
- 51单片机lcd1602屏protues仿真keil工程源码.zip
- 51单片机报警器与旋转灯protues仿真keil工程.zip
- 51单片机protues仿真驱动屏幕滚动显示文字keil工程源码.zip
- 51单片机电机转速表设计protues仿真.zip
- 51单片机电机控制_L298 protues仿真.zip
资源上传下载、课程学习等过程中有任何疑问或建议，欢迎提出宝贵意见哦~我们会及时处理！
点击此处反馈
