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| 內容簡介： |
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Location information is playing a more and more important role in people’s life. There are many application scenarios depending on positioning in the future 5G communications, such as Virtual Reality VR, Internet of Things IoT, Internet of Vehicles IoV and so forth. Especially, indoor positioning has attracted more attentions because of its huge business potential while there are no mature and versatile solutions. This book aims to identify the requirements of indoor positioning in the future work, present the potential network architecture and key technologies that can fulfill the requirements, and research the localization network programming and deployment.Finally, this bookprovides some solutions about the positioning equipment research and deployment, and the network programing. Additionally, some test and validation cases are presented for reference.（主要内容翻译：本书旨在确定未来工作中对室内定位的要求，提出能够满足需求的潜在网络体系结构和关键技术，并对定位网络规划与部署进行研究。*后，本书还对定位设备的研究与部署，以及网络编程等问题提出了一些解决方案。此外，还提供了一些测试和验证用例以供参考。）
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| 關於作者： |
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陈诗军，中兴通信资深技术专家，CCSAST7 副主席、室内定位工作组组长；北斗技术与应用委员会副主席。1996~2017，先后参与硬件式容错可靠性测评技术、舰艇网络系统抗毁性研究、2G3G4G5G技术研究与产品研发等20多个项目与课题，获得深圳科技贡献奖章（2015、2016）、广东省科技进步奖二等奖（2017，第一完成人）、深圳科技进步一等奖（2015，第一完成人）、中国通信学会科技奖（2017，第四完成人）等10项科技奖。 2010~2012完成了 IMT-Advanced频谱聚合技术研发国家重大专项课题，排名第2，已验收等三个国家重大专项项目。同时作为项目负责人负责 IMT-ADV验证平台、关键技术验等三项公司战略研究项目（2010~2012，排名第1）。先后完成多天线MU-MIMO、CoMP 技术研究和原型验证等，巴塞电信展上展示了业界第一个CoMP原型机；研制了行业首个大容量网络级无线验证系统，获得深圳科技一等奖，研制了无线技术与产品支撑平台（基础创新平台），获得了广东省科技二等奖。 2013~2017负责高精度室内无线定位技术研究，提出了运营商级室内定位解决方案-带内定位网技术。负责带内地面定位网技术（2015 深圳重大技术攻关课题，排名第1），面向亚米级位置服务5G技术研究（2016国家重大科技专项课题，排名第1）、以及承担通信定位一体化试验基站（2015国家863子课题，排名第1）以及室内混合智能定位技术研究与设备研发（2016 国家十三五重点研发计划子课题， 排名第1）。 LTE无线定位研究获得中国通信学会科技奖。 工作期间共申请专利60余项，其中作为第一发明人申请专利39项、在核心期刊等刊物上发表论文16篇，其中近年发表10篇。
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| 目錄：
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Chapter 1 Introduction 1
Chapter 2 Current Status, Challenges and Requirements 4
2.1 Current Status of Indoor Positioning 4
2.2 Challenges of Indoor Positioning 8
2.3 Requirements 12
Reference 14
Chapter 3 Localization Network Architecture 16
3.1 Universal Positioning Architecture 16
3.2 Integrated System of Navigation and
Communication 20
3.3 Future Development of Indoor Positioning 22
Reference 25
Chapter 4 Key Technologies 26
4.1 Localization Signal Design 26
4.2 Signal Measurement and Localization
Technologies 33
4.3 Synchronization Technologies 50
4.4 Channel Modeling 56
4.5 Tracking and Map Matching 62
4.6 Intelligent Hybrid Localization 68
4.7 Localization Technologies in 5G 75
Reference 82
Chapter 5 Localization Network Programming and
Deployment 89
5.1 Equipment Research and Development 89
5.2 Network Programming Solutions 96
5.3 Test and Validation 104
Reference 115
Chapter 6 Summary 117
Chapter 7 Glossary 119
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| 內容試閱：
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Location information is playing a more and
more important role in peoples life. There are many application scenarios
depending on positioning in the future 5G communications, such as Virtual
Reality VR, Internet of Things IoT, Internet of Vehicles IoV and so
forth. Especially, indoor positioning has attracted more attentions because of
its huge business potential while there are no mature and versatile solutions.
This white paper aims to identify the requirements of indoor positioning in the
future work, present the potential network architecture and key technologies
that can fulfill the requirements, and research the localization network
programming and deployment.
By now, there have been various positioning
technologies corresponding to different requirements and scenarios. Generally,
indoor positioning faces the challenges of location accuracy, cost, coverage
range, latency and the complexity of indoor environments resulting from
multipath propagation and frequent environment changes. A brief summary of the
main challenges and solutions is given below.
Localization network architecture design
? A
universal positioning architecture includes two parts of information extraction
and position calculation.
? The
integration of multiple positioning functiona
lities seems inevitable and requires the
convergen
ce of positioning standards that ensure
multi-stand and multi-vendor interoperability.
Signal measurement method
? Wireless
positioning systems estimate the location by mapping the signal features to the
space location.
? These
approaches need to extract the wireless signal features, such as RSS, TOA,
TDOA, and AOA.
Localization algorithm
? In
wireless positioning system, the location estimation method is the core
component which aims to mapping the signal metrics RSSTOA
TDOAAOA into 2D3D location.
? The
typical wireless positioning techniques incl
ude trilateration, triangulation,
fingerprinting also known as scene analysis, and proximity.
Synchronization technologies
? Synchronization
technology is one of the key research areastechnologies for high accuracy
positioning systems. Approximately every 3ns of synchronization precision
decreasing leads to 1 meter distance-measuring error.
? Some
candidate techniques are considered on the whole in order to control the
end-to-end time error in synchronization networks include enhanced GNSS
technique, enhanced reference time source, enhanced auxiliary frequency
technique, enhanced PTP technique, etc.
Channel modeling
? The
implementation of the channel simulation is helpful in decreasing the amounts
of manpower, material and the cost of time. Besides, it is important to realize
the high-precision position
ing and the elements layout.
? A
representative technology in certain models is the ray tracing technique, which
is based on the geometrical optics theory.
Tracking and map matching
? The
continuous and dynamic location estimation or tracking is essential，and is
modeled to be a state sequence estimation. The system can adopt the Bayesian
estimation method to analyze and optimize the estimation problems.
? The
positioning system usually has the map information to display the location
content. The map typically includes the roads, structures, facilities and
various landmarks, which can be used to constrain the targets movement or
correct the estimation error.
Intelligent hybrid localization
? The
new-generation indoor localization techno
logy combined with multiple locating
information sources including the pressure sensor, direction sensor and optical
image sensor etc., has become the focus of further research.
Prediction of localization technologies in
future 5G communications
? With
the emergence of D2D communication, each mobile device can make additional
short-distance range measurements with respect to its nearby devices, and
cooperates with those neighbors for positional inference.
? With
the development of full duplex technology and combination of round-trip time
technology, the distances between the nodes in wireless networks can be obtain
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