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高速铁路SFN MIMO信道模型:性能分析与应用
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高速铁路的SFN MIMO信道模型是本篇研究论文在第32届URSIGASS会议上于2017年8月19日至26日在蒙特利尔提出并探讨的关键技术。该研究主要关注在高速铁路场景中实施单频网(Single Frequency Network, SFN)时的多输入多输出(Multiple Input Multiple Output, MIMO)信道建模。SFN是一种通过同步传输多个相同频率信号来提高无线网络覆盖和容量的方法,特别是在广覆盖需求高的高速铁路环境中。 论文首先提出了一个改进的SFN MIMO信道模型,考虑到高速铁路环境中的散射特性,每个信道路径被建模为瑞利衰落(Ricean fading)通道。这种模型结合了MIMO技术和修改后的SFN,更准确地反映了实际高速铁路场景下的无线通信特性。作者重点分析了基于此模型的MIMO架构,并对其性能进行了深入研究。 在研究过程中,论文着重考察了MIMO系统在2x2配置下的性能,即两个发射天线和两个接收天线之间的通信。结果显示,尽管面临高速移动和复杂环境的影响,MIMO技术依然能够在高速铁路的SFN场景中保持其有效性。通过仿真验证,2x2 MIMO系统的系统吞吐量得到了显著提升,证明了其在提高数据传输速率和抗干扰能力方面的优势。 此外,文章还可能讨论了与传统非MIMO系统相比,采用SFN MIMO技术对频谱效率、覆盖范围和可靠性的影响,以及可能存在的挑战,如同步精度、多用户干扰管理和网络规划等。总体而言,这篇论文为高速铁路通信系统的优化设计提供了理论支持,对未来的无线通信技术发展具有重要意义。
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32
nd
URSI GASS, Montreal, 19-26 August 2017
SFN MIMO Channel Model for High-speed Railway
Jinmeng Zhao
1
, Lei Xiong
1
, Yu Zhang
1
, Ting Zhou
2
, Yuanchun Tan
3
1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing 100044, China
2. Key Laboratory of Wireless Sensor Network & Communication, Shanghai Institute of Microsystem and Information
Technology, Chinese Academy of Sciences, 865 Changning Road, Shanghai 200050, China
3. Beijing Xinwei Telecom Technology Group Co., Ltd, Beijing 100094, China
{lxiong}@bjtu.edu.cn
Abstract
A SFN MIMO channel model is proposed and analyzed
for high-speed railway SFN scenario in this paper.
Considering the influence of scattering components, every
tap of the modified SFN channel is Ricean fading channel.
Thus, this model combines the MIMO channel with the
modified SFN channel which fits actual high-speed
railway scenario. Based on the SFN MIMO channel
model, the MIMO architecture is studied and the
performance of the MIMO system is analyzed. The
simulation results show that the MIMO technology is still
applicable and the system throughput in the 2×2 MIMO
channel can be doubled compared to SISO when the
placement of antennas is perpendicular to the rail.
1. Introduction
In recent years, the demands and challenges for
communication in the high-speed railway is increasing.
Therefore, it is very important to carry out MIMO channel
simulation in high-speed railway scenarios as a part of
development of Long Term Evolution (LTE) system. In
view of LTE’s advanced network architecture, the MIMO
technique is introduced in the evolutionary process, but
there are not many MIMO channel models for high-speed
railway scenarios. The existing MIMO channel models
are not suitable for high-speed railway scenarios. In this
case, it is necessary to study the applicability of MIMO
technology in a specific scenario.
The high-speed railway scenario mainly has differences in
the aspects of propagation scenarios, coverage, and
Doppler frequency shift and so on. Compared with the
public mobile communication system, the high-speed
railway scenario has its unique characteristics: Radio
propagation environment is different: For example, in the
high-speed railway viaduct scenario, the scenario is more
open, having fewer obstacles, so the radio propagation
mode is LoS path-based, with less scattering components;
Different ways of coverage: Along the high-speed railway,
the base station is deployed along the railway status, and
it is linearly covered and close to the railway track (10-
50m); High-speed movement results in significant
Doppler frequency shift effect. Scenarios and channel
characteristics of high-speed railway communication
system are an indispensable part of the study. The
B3G/4G system uses a stochastic statistical channel model
based on geometry, such as SCM/SCME [1-2] and
WINNER model [3]. The WINNER defines 13 kinds of
scenarios consisting of the city micro-cellular, suburban
macro cell and so on [4-5]. In the RAN4 # 74 meeting of
3GPP TSG-RAN WG4, four scenarios were determined
to be used as the basic scenario for the research project
with a number of revisions written at # 77 TR [6].
This paper is organized as follows. Combining MIMO
model based on correlation matrix with SFN channel
model, a Modified Channel Model for SFN is described in
Section 2. Section 3 analyses the performance of the
system under SISO and MIMO conditions, such as the
efficiency (throughput). Section 4 concludes the paper.
2. Channel Models
2.1 MIMO model based on correlation matrix
A common technique for modeling multipath propagation
is assuming that arriving waves from similar directions
and delays are grouped into clusters [7]. Considering a
downlink MIMO link. The base station (BS) and the
mobile station (MS) use uniform linear arrays (ULAs)
with M and N antennas, which are assumed to be
omnidirectional. The transmitting signals are denoted by
the vector:
12
, ,...
T
M
s t s t s t s t
, where s
m
(t) is
the signal at the mth antenna port and [ ⋅ ]
T
denotes
transposition, Similarly, the receiving signals are
12
, ,...
T
N
y t y t y t y t
. The
MIMO
NM
tC
H
of
a broadband MIMO channel is represented as follows:
MIMO
1
L
ll
l
tt
HA
(1).
where
l
is the lth path’s relative delay. A
l
describes the
connection between the MS and the BS of the lth path,
and it’s expressed as:
11 1
1
ll
M
l
ll
N NM
A
(2).
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