大规模MIMO系统的3D信道建模和测量

发布时间：2021-12-24 20:46

　　大规模多输入多输出（MIMO）是指能够使用几百根天线同时为第五代（5G）移动通信系统的一个或多个无线宽带终端提供大量的数据流的设计系统,该系统使用更简单和拟线性算法来精确地实现波束成形和解码。在大规模MIMO网络成功开发之前,有一些基本的问题需要得到更好的理解,比如信道建模、相关性设计等。为了对将来的大规模MIMO无线通信系统的有个更好的评估和设计,我们需要精确的信道模型来描述无线传播信道。在这篇论文中,我们详细回顾了大规模MIMO系统,重点介绍了系统的关键部件和研究方向,其中包括:在天线单元中使用波束方向图的优点;单个用户大规模MIMO系统中的预编码操作,该预编码也同时考虑波束方向图对发射和接收天线单元的影响。此外,结合不同天线单元垂直空间相关的波束方向图,我们还提出了一个实用的框架来推导三维（3D）信道模型的统计特性。由于该波束方向图使用了不同相位激励方向（DoTS）的偶极子天线单元,对与团簇相关的射线使用了不同的相关权重,因此,可以为每个天线元件提供不同的到达仰角（EAoAS）和偏离仰角（EAoD）。最后,本论文考虑了不同用户之间的地理位置相关性,将SU-大规模MIMO信道模型推... 

【文章来源】：上海交通大学上海市 211工程院校 985工程院校 教育部直属院校

【文章页数】：187 页

【学位级别】：博士

【文章目录】：
摘要
Abstract
Abbreviations
Physical Constants
Symbols
Chapter1 Introduction
    1.1 Background
    1.2 Motivation
    1.3 Contributions
    1.4 Thesis Organisation
Chapter2 The Traditional Ray Tracing SCModels for Massive MIMO Communications on Campus Scenarios for Outdoor and Outdoor-to-Indoor
    2.1 Introduction
    2.2 Overview of Theoretical SCM Model for MIMO System
        2.2.1 General Parameters
            2.2.1.1 Set Environment, Network Layout, and AntennaArray Parameters
            2.2.1.2 Large Scale Parameters
            2.2.1.3 Small Scale Parameters
            2.2.1.4 Generation of 3-D Channel Coefficient
            2.2.1.5 Outdoor 3-D Massive MIMO Channel Models
            2.2.1.6 Outdoor-to-Indoor 3-D Massive MIMO ChannelModels
    2.3 Summary
Chapter3 Outdoor Channel Measurements and Models for SU-Massive MIMO on Different Scenario: Model, Design,Implementation, and Drawbacks
    3.1 Background Information on Massive MIMO
        3.1.1 MIMO Orthogonal Frequency Division Multiplexing (OFD-M)
        3.1.2 Frame Structure
        3.1.3 Physical Channels and Signals in Radio Frame
        3.1.4 Signal Measuring
        3.1.5 Angle of Arrival and Angle of Departure
    3.2 Generic Hardware and Processing Partitioning
        3.2.1 Software-Defined Radio platform and Basics
        3.2.2 Communication System Block Diagram
        3.2.3 USRP Module Block Diagram
            3.2.3.1 Software Design
            3.2.3.2 Hardware Design
        3.2.4 Implementation Features
            3.2.4.1 Transmitter
            3.2.4.2 Receiver
        3.2.5 Measurement’s Setup Parameters
            3.2.5.1 LAB-View RX Tool
        3.2.6 Outdoor Measurement Scenarios
    3.3 Scenario of Outdoor SU-Massive MIMO Performance EvaluationModel
        3.3.1 Wireless Propagation and Fading Model
            3.3.1.1 Large Scale Fading
        3.3.2 Path loss Modelling
        3.3.3 Massive MIMO Antenna Configuration
    3.4 Measurement-Based Channel Characterization for SU-Massive MI-MO Wireless Communications On Campus Scenario
        3.4.1 Signal Model
        3.4.2 Synchronization
            3.4.2.1 Coarse Timing Synchronization
            3.4.2.2 Primary and Secondary Synchronization Signal
        3.4.3 Channel Estimation Procedure
            3.4.3.1 LMMSE Algorithms for Channel Estimation
            3.4.3.2 Joint Time-Frequency Two-Dimensional IterativeWiener Filtering (IWF) Channel Estimation
        3.4.4 Physical Channel Performance
        3.4.5 Statistical Result and Discussion
            3.4.5.1 Spatially Correlation Channel
            3.4.5.2 Channel Capacity
    3.5 Research Gaps in Massive MIMO Channel Measurements and Models
    3.6 Summary
Chapter4 A Novel Non-Stationary MU-Massive MIMO Channel Models for Out-door Scenarios
    4.1 Introduction
    4.2 Signal Model and Antenna Configuration/Positioning
        4.2.1 3-D AES and Antenna Element’s Positioning
        4.2.2 3-D Signal Model
        4.2.3 3-D Beam Pattern
    4.3 3-D Vertical Received Spatial Correlation
        4.3.1 Update UEs Movements
    4.4 A 3-D Non-Stationary MU-Massive MIMO Model Using BeamPattern
        4.4.1 The 3-D Non-Stationary MU-Massive MIMO Channel Mod-el
            4.4.1.1 NLOS Complex Gains
            4.4.1.2 LOS Complex Gains
        4.4.2 Result and Discussion for 3-D Beam Pattern Multi-PolarizedMassive MIMO
            4.4.2.1 Path Models
            4.4.2.2 Capacity Correlation
            4.4.2.3 ECC and Correlation versus Receiving Antenna Spacing
            4.4.2.4 Generation of a Time Varying Channel and Characteristics
    4.5 A 3-D Non-Stationary Distributed MU-Massive MIMO ChannelModel
        4.5.1 The Non-Stationary Distributed MU-Massive MIMO Model
        4.5.2 UE Dropping
        4.5.3 Result and Discussion for 3-D Distributed MU-MassiveMIMO
            4.5.3.1 Multipath Propagation Channel
            4.5.3.2 Channel Capacity on Distributed MU-MassiveMIMO
            4.5.3.3 RSRP, RSRQ, RSSI, and SINR Simulation
    4.6 Summary
Chapter5 A Novel Stationary MU-Massive MIMO Channel Models for Outdoor-to-Indoor Scenario
    5.1 Introduction
    5.2 Signal Model, Indoor Testbed with Antenna Configurations
        5.2.1 Antenna Pattern
            5.2.1.1 Transmit Antenna Array
            5.2.1.2 Receive Antenna Array
    5.3 Channel Properties
        5.3.1 Small Scale Fading
        5.3.2 Outdoor-to-Indoor Multipath Delay Properties
        5.3.3 Delay of the Clusters
        5.3.4 Spatial Correlation and Capacity
    5.4 A 3-D Stationary Massive MIMO Model for Outdoor-to-IndoorScenario
        5.4.1 Outdoor 3-D Massive MIMO Channel Models
            5.4.1.1 NLOS Outdoor Complex Gains
            5.4.1.2 LOS Outdoor Complex Gains
        5.4.2 Indoor 3-D Massive MIMO Channel Models
            5.4.2.1 NLOS Indoor Complex Gains
            5.4.2.2 LOS Indoor Complex Gains
        5.4.3 Result and Discussion for 3-D Indoor Multi-User MassiveMIMO System
            5.4.3.1 Multipath Propagation Channel
            5.4.3.2 Channel Properties and Profile
            5.4.3.3 Indoor Channel Capacity
    5.5 Summary
Chapter6 Conclusions and Future Work
    6.1 Summary of Results
    6.2 Future Work
Bibliography
Acknowledgements
Publications


【参考文献】：
期刊论文
[1]Recent advances and future challenges for massive MIMO channel measurements and models[J]. Cheng-Xiang WANG,Shangbin WU,Lu BAI,Xiaohu YOU,Jing WANG,Chih-Lin I.  Science China（Information Sciences）. 2016(02)



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