IoT Signal Detection
Description
Comprehensive reference covering signal detection for random access in IoT systems from the beginner to expert level
With a carefully balanced blend of theoretical elements and applications, IoT Signal Detection is an easy-to-follow presentation on signal detection for IoT in terms of device activity detection, sparse signal detection, collided signal detection, round-trip delay estimation, and backscatter signal division, building progressively from basic concepts and important background material up to an advanced understanding of the subject. Various signal detection and estimation techniques are explained, e.g., variational inference algorithm and compressive sensing reconstruction algorithm, and a number of recent research outcomes are included to provide a review of the state of the art in the field.
Written by four highly qualified academics, IoT Signal Detection discusses sample topics such as:
- ML, ZF, and MMSE detection, Markov chain Monte Carlo-based detection, variational inference-based detection, compressive sensing-based detection
- Sparse signal detection for multiple access, covering Bayesian compressive sensing algorithm and structured subspace pursuit algorithm
- Collided signal detection for multiple access using automatic modulation classification algorithm, round-trip delay estimation for collided signals
- Signal detection for backscatter signals, covering central limited theorem-based detection including detection algorithms, performance analysis, and simulation results
- Signal design for multi-cluster coordination, covering successive interference cancellation design, device grouping and power control, and constructive interference-aided multi-cluster coordination
With seamless coverage of the subject presented in a linear and easy-to-understand way, IoT Signal Detection is an ideal reference for both graduate students and practicing engineers in wireless communications.
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Persons
Rui Han, PhD, is an Associate Professor at the School of Cyber Science and Technology, Beihang University.
Jingjing Wang, PhD, is a Professor at the School of Cyber Science and Technology, Beihang University.
Lin Bai, PhD, is a Professor at the School of Cyber Science and Technology, Beihang University.
Jianwei Liu, PhD, is a Professor at the School of Cyber Science and Technology, Beihang University.
Content
List of Figures xi
List of Algorithms xvii
About the Authors xix
Foreword xxi
Preface xxiii
Acknowledgements xxv
Acronyms xxvii
1 Introduction 1
1.1 IoT in 5G 1
1.1.1 What Is IoT 1
1.1.2 Applications of IoT 2
1.1.3 Future of IoT 3
1.2 IoT Networks 4
1.3 Characteristics of IoT Signals 6
1.4 Outline 8
2 Background of IoT Signal Detection 11
2.1 Random Access 11
2.1.1 Grant-based Random Access 11
2.1.2 Grant-free Random Access 14
2.2 Signal Detection Methods 16
2.2.1 System Model 17
2.2.2 ML Detection 18
2.2.3 ZF Detection 22
2.2.4 MMSE Detection 25
2.2.5 MCMC Detection 28
2.2.6 VI Detection 31
2.2.7 CS Detection 34
2.3 Conclusion and Remarks 38
3 Sparse Signal Detection for Multiple Access 39
3.1 System Model 39
3.2 Sparse Signal Detection 41
3.2.1 Tree Search-based Approach 41
3.2.2 VI Detection Algorithm 44
3.3 Performance Analysis 48
3.3.1 Complexity Analysis 48
3.3.2 VI Detection Performance Analysis 49
3.4 Simulation Results 55
3.5 Conclusion and Remarks 61
4 Collided Signal Detection for Multiple Access 63
4.1 System Model 63
4.2 Automatic Modulation Classification-based Detection 66
4.2.1 Preamble Sequence Detection 66
4.2.2 HOCs-based AMC Approach for Collision Recognition 68
4.2.3 Data Decoding with SIC 69
4.3 Performance Analysis 71
4.4 Simulation Results 78
4.5 Conclusion and Remarks 86
5 Multiple Delay Estimation for Collided Signals 89
5.1 System Model 89
5.2 Multiple Delay Estimation 92
5.2.1 ML Detection Algorithm 92
5.2.2 CAVI Detection Algorithm 95
5.2.3 MCMC Detection Algorithm 99
5.3 Signal Number Estimation and Channel Estimation 100
5.4 Simulation Results 102
5.4.1 CAVI Simulation Results 102
5.4.2 MCMC Simulation Results 109
5.5 Conclusion and Remarks 115
6 Detection and Division for Backscatter Signals 117
6.1 System Model 117
6.2 Central Limit Theorem-based Signal Detection 122
6.2.1 Activity Detection Algorithm 123
6.2.2 Signal Detection Algorithm 126
6.2.3 Performance Analysis 127
6.3 Simulation Results 128
6.4 Conclusion and Remarks 134
7 Analysis and Optimization for NOMA Signals 137
7.1 System Model 137
7.2 Throughput and Power Consumption Analysis 139
7.2.1 Throughput Analysis 139
7.2.2 Power Consumption Analysis 140
7.3 Energy Efficiency Performance Optimization 141
7.4 Simulation Results 145
7.5 Conclusion and Remarks 148
8 Signal Design for Multicluster Coordination 149
8.1 Multi-cluster Coordination in IoT 149
8.2 Multi-cluster Coordination with NOMA 152
8.2.1 Multi-cluster Coordination NOMA Design 152
8.2.2 Multi-cluster Coordinated NOMA Resource Allocation 153
8.3 CI-aided Multi-cluster Coordination with Interference Management 156
8.3.1 CI Signal Design 156
8.3.2 CI Design for Multi-cluster Coordination 158
8.4 FutureWorks 161
8.5 Conclusion and Remarks 162
9 Conclusion of the Book 163
References 165
Index 175
1
Introduction
- In the present era, as Internet applications continue to evolve, studies on Internet of Things (IoT) have represented a growing field. This is particularly driven by the advancements in the latest generation of information technology, which leads to various innovative paradigms such as smart agriculture, smart health, and smart logistics. As a result, the concept of intelligent interconnectivity between all objects has become a reality. This has led to a profound transformation in the way people live, work, and travel, ushering in a new era of possibilities.
1.1 IoT in 5G
1.1.1 What Is IoT
IoT refers to the technique of using various devices, such as radio frequency identification (RFID), sensors to collect necessary information of things or progresses, then transmitting the collected data through the network, to achieve the ubiquitous connection between objects and people, objects and objects [1].
The concept of IoT was initially proposed by the Massachusetts Institute of Technology in 1999 [2]. At its early stages, IoT referred to the network created by the RFID technology and equipment. By incorporating the Internet and adhering to agreed-upon communication protocols, this network facilitated intelligent identification and management of product information, enabling seamless interconnectivity [3].
However, with ongoing technological advancements and application development, the scope of IoT has been broadened. In its modern aspect, IoT encompasses the integration of perception, identification, and control of interconnected objects. This integration, combined with networking and intelligent processing capabilities, enables the formation of highly intelligent decision-making systems [4].
As outlined in the White Paper on IoT published by the China Academy of Information and Communications Technology (CAICT) [5], IoT represents an expansive application and network extension of existing communication networks and the Internet. Through the utilization of perceptual technology and intelligent devices, IoT enables the perception and identification of the physical world. By leveraging network transmission and interconnectivity, IoT facilitates computation, processing, and knowledge mining. As a result, it enables seamless interaction and connectivity between individuals and objects, as well as between objects themselves. This, therefore, enables real-time control, precise management, and informed decision-making processes.
Regarding the fifth generation (5G) of wireless technology, advancements of IoT primarily stem from innovations in wireless and network technologies [6]. Within the field of wireless technology, the industry has placed particular emphasis on large-scale antenna arrays, ultra-dense networking, innovative multiple access techniques, and full spectrum access. Network technology has also witnessed significant progress, with the widespread recognition of a new network architecture based on software-defined networking (SDN) and network function virtualization (NFV) [7].
Furthermore, several key technologies have been exploited as important and promising contributors to 5G, including filter-based orthogonal frequency division multiplexing (F-OFDM), filter bank multicarrier (FBMC), full duplex and flexible duplex, multivariate low-density parity check (LDPC) codes, network coding, and polarization codes.
From a network architecture perspective, 5G inherits the overall characteristics of the fourth generation (4G), encompassing access networks, core networks, and upper-layer applications. However, to accommodate the diverse requirements of IoT, 5G has introduced new key technologies in both the core network and access network domains, bringing on technological innovations and network advancements.
1.1.2 Applications of IoT
Currently, there has been a successful combination between 5G communication technology and IoT [8]. This integration has brought on widespread applications in various domains including intelligent manufacturing, wireless healthcare, and smart logistics. The inherent advantages of 5G and IoT, such as enhanced efficiency and reliability, have significantly propelled the improvement of practical applications in these areas. The utilization of 5G-based IoT is expected to incredibly enhance the overall quality of life and transform our work and lifestyle practices fundamentally.
In recent years, the widespread adoption of IoT, particularly in the industrial area, has become increasingly prevalent [9]. A prime example of the combination between 5G communication technology and IoT is the application of wireless healthcare, which has greatly facilitated the life of individuals. The integration of IoT technology into medical devices has brought on an escalating demand for superior communication quality in remote control scenarios [10].
During the era of 4G communications, exposure to issues of signal quality has been shown to be related to adverse effects on the continuity and safety of the entire diagnostic and treatment process. Thankfully, the advent of 5G networks has significantly improved signal quality, offering low-latency and reliable connections. This enhancement enables medical professionals to accurately and promptly assess patients' conditions in remote diagnosis, thanks to high-resolution images and videos, and provide precise feedback in wireless healthcare. Besides, the utilization of remote medical devices in scientific surgical procedures ensures a high-quality service for patients.
Moreover, 5G communications have emerged as powerful platforms for autonomous driving systems. With the benefits of 5G, autonomous vehicles can strengthen their perception, decision-making, and control functions to the edge cloud. This architecture allows the processing and dissemination of data to be carried out utilizing the computational capabilities of the edge cloud, thus reducing the reliance on vehicle sensors [11].
Furthermore, the remote driving within the field of Internet of Vehicles (IoV) becomes a key instrument in efficient vehicle control and monitoring from production scheduling centers. The incorporation of remote driving not only ensures the driving safety and well-being of individuals but also gives significant advancements within the automotive industry, which promotes convenient transportation for individuals and generates economic benefits for the automotive sector.
1.1.3 Future of IoT
The Narrowband Internet of Things (NB-IoT) technique has been a major contributor in driving the widespread implementation of IoT within various domains, e.g., industrial interconnection, and improving people's quality of life. This advancement has led to the establishment of a innovative industrial ecosystem and substantial commercial expansion [12].
Looking ahead, the future of IoT promises to experience significant transformations in the next two decades due to the continuous development of innovative technologies. One prominent example is the forthcoming realization of large-scale vehicle and utility automation. This progress will encompass various facets, such as smart grids for energy production, efficient waste management systems, and intelligent environmental monitoring, all aimed at reducing greenhouse gas emissions and pollution.
While the utilization of 5G network in IoT offers numerous benefits and shows remarkable potential for future advancements, it is crucial to acknowledge the issues that arise during the practical implementation of a 5G-based IoT architecture. These issues include inadequate communication security, significant investment costs, increasing energy consumption, and limited availability of high-frequency resources, all of which contribute to the complexities associated with deploying IoT networks.
These difficulties primarily stem from the expansion of network infrastructure, effective management of IoT equipment, and efficient processing of the vast amount of data generated by the extensive deployment of mechanical devices within the IoT ecosystem. Furthermore, interoperability and heterogeneity pose additional challenges within the context of IoT. For instance, seamless integration of heterogeneous networks remains a persistent issue, inhibiting effective connectivity among these networks. In particular, the interoperability problem is increasingly recognized as a serious concern in the communication and exchange of information between numerous mechanical devices and intelligent networks, as well as in establishing connections with various applications. The lack of standardized protocols and compatible interfaces hinders smooth interoperability. Moreover, there are potential concerns regarding information security. Ensuring data integrity and confidentiality within the IoT communication system presents a significant challenge, as vulnerability in the network infrastructure and device ecosystem may compromise the security of the transmitted data.
To effectively tackle the challenges arising from the application of IoT technology in the 5G network and ensure the efficient utilization of IoT systems, it is imperative to establish unified standards for wireless communications, data collection, and security management. These standards should satisfy the specific requirements of 5G IoT applications and facilitate the advancement of robust security management and control mechanisms.
Currently, researches on 5G-based IoT networks are in their early stages and lack a mature research...
