LPWAN Technologies for IoT and M2M Applications

Description

Low power wide area network (LPWAN) is a promising solution for long range and low power Internet of Things (IoT) and machine to machine (M2M) communication applications. The LPWANs are resource-constrained networks and have critical requirements for long battery life, extended coverage, high scalability, and low device and deployment costs. There are several design and deployment challenges such as media access control, spectrum management, link optimization and adaptability, energy harvesting, duty cycle restrictions, coexistence and interference, interoperability and heterogeneity, security and privacy, and others. LPWAN Technologies for IoT and M2M Applications is intended to provide a one-stop solution for study of LPWAN technologies as it covers a broad range of topics and multidisciplinary aspects of LPWAN and IoT. Primarily, the book focuses on design requirements and constraints, channel access, spectrum management, coexistence and interference issues, energy efficiency, technology candidates, use cases of different applications in smart city, healthcare, and transportation systems, security issues, hardware/software platforms, challenges, and future directions. LPWAN Technologies for IoT and M2M Applications Copyright Contents List of contributors About the editors Preface Acknowledgment 1 Introduction to low-power wide-area networks 1.1 Introduction 1.2 Intelligent applications and services 1.2.1 Application requirements 1.3 Wireless access 1.4 Low-power wide-area network application characteristics 1.4.1 Coverage 1.4.1.1 Traffic characteristics 1.4.1.2 Coverage 1.4.1.3 Location identification 1.4.1.4 Security and privacy 1.4.2 Capacity 1.4.2.1 Capacity and scalability 1.4.3 Cost 1.4.3.1 Cost-effectiveness 1.4.4 Low-power operations 1.4.4.1 Energy-efficient operations and low-power sources 1.4.4.2 Reduced hardware complexity 1.4.5 Additional specific requirements 1.4.5.1 Range of solution options 1.4.5.2 Operations, interrelationships, and interworkings 1.5 Summarized objectives and expectations for low-power wide-area network References 2 Design considerations and network architectures for low-power wide-area networks 2.1 Introduction 2.2 Design considerations for low-power wide-area networks 2.2.1 Traffic characteristics 2.2.2 Capacity and densification 2.2.3 Energy-efficient operations and low-power sources 2.2.4 Coverage 2.2.5 Localization 2.2.6 Security and privacy 2.2.7 Reduced device hardware complexity 2.2.8 Range of solutions options 2.2.9 Operations, interrelationships, and interworking 2.3 Internet of things/low-power wide-area network layer model 2.4 Low-power wide-area network topologies and architecture 2.4.1 Low-power wide-area network topologies 2.4.2 Major architectures in low-power wide-area network technologies 2.4.3 Mixed hybrid architectures 2.5 Introduction to proprietary and standards-based solutions 2.5.1 Proprietary technologies 2.5.1.1 Sigfox 2.5.1.2 Ingenu 2.5.1.3 Telensa 2.5.1.4 Qowisio 2.5.1.5 Nwave 2.5.2 Standards-based technologies 2.5.2.1 LoRa and LoRaWAN 2.5.2.2 Weightless 2.5.2.3 Narrowband Internet of things 2.5.2.4 LTE-M 2.5.2.5 DASH7 2.5.2.6 NB-Fi 2.5.2.7 Enhanced coverage–global system for mobile Internet of things 2.5.2.8 IEEE 802.15.4k 2.5.2.9 IEEE 802.15.4g References 3 LoRaWAN protocol: specifications, security, and capabilities 3.1 Technical overview of LoRaWAN specifications 3.2 LoRaWAN link layer 3.3 Scaling LoRaWAN networks 3.3.1 LoRaWAN star topology with receive diversity is the key to scaling in an unlicensed spectrum 3.3.2 Role of adaptive data rate 3.3.3 LoRaWAN network capacity and scaling 3.4 LoRaWAN regional parameters 3.5 Activation and roaming 3.6 Network-based and multitechnology geolocation 3.6.1 Geolocation is a massive opportunity 3.6.2 Vast choice of technologies 3.6.3 LoRaWAN multitechnology geolocation is a game changer 3.7 Using LoRaWAN for firmware upgrade over the air 3.7.1 Introduction 3.7.2 LoRaWAN FUOTA principle 3.7.3 LoRaWAN multicast groups 3.7.4 Transporting a file to a multicast group 3.8 Security 3.9 LoRaWAN certification Author Contribution References 4 Radio channel access challenges in LoRa low-power wide-area networks 4.1 Purpose of this chapter 4.2 Review of LoRa physical layer 4.2.1 LoRa physical layer (PHY) structure 4.2.1.1 Encoding 4.2.1.2 Whitening 4.2.1.3 Interleaving 4.2.1.4 Chirp spread spectrum modulation 4.2.1.5 Chirp spread spectrum demodulation 4.2.1.6 Packet structure and time on air 4.2.2 PHY performance 4.2.3 Interference in LoRa 4.2.4 Orthogonality of LoRa transmissions 4.3 Dealing with interferences in LoRa 4.3.1 Impact of adaptive data rate 4.3.2 Impact of duty-cycle limitation 4.3.3 Interference mitigation: capture effect 4.3.3.1 Capture effect simulations 4.3.3.2 Capture effect experimentations 4.3.3.2.1 Capture effect setting 4.3.3.2.2 Results Test 1 4.3.3.2.3 Results Test 2 4.3.3.2.4 Results Test 3 4.3.3.2.5 Test in indoor conditions 4.3.4 Interference mitigation: interference cancellation 4.4 Channel access: sharing the bandwidth 4.4.1 Review of media access control mechanisms 4.4.1.1 IEEE 802.11 4.4.1.2 IEEE 802.15.4 4.4.2 Clear channel assessment in LoRa 4.4.3 Adaptation from 802.11 4.4.4 Channel activity detection reliability issues 4.4.5 A solution to protect long messages 4.5 Studying large-scale LoRa deployments 4.5.1 The CupCarbon architecture 4.5.1.1 Two-dimensional/three-dimensional city model module 4.5.1.2 Radio channel propagation module 4.5.1.3 Interference module 4.5.2 LoRa PHY/media control access integration in CupCarbon 4.6 Conclusions 4.7 Acknowledgments References 5 An introduction to Sigfox radio system 5.1 Internet of things, a new usage for the radiocommunication industry 5.2 Low-power wide-area network: a new paradigm in radio network engineering 5.3 Ultra-narrowband: a disruptive way to use radio spectrum 5.3.1 Tuning: an old answer to capacity challenge 5.3.2 The 1-ppm limit 5.3.3 Ultra-narrowband benefits for low-power wide-area networks 5.3.3.1 Frequency channel allocation revisited 5.3.3.2 Capacity given by base station processing power 5.3.3.3 Complexity pushed back into core network 5.3.3.4 Ultra-narrowband robustness in unlicensed spectrum 5.4 Triple diversity ultra-narrowband, the Sigfox communication rules 5.4.1 Protocol versus communication rules 5.4.2 Uplink communication rules 5.4.2.1 Six steps to build an uplink radio burst 5.4.2.2 Small payload size for Internet of things usage 5.4.2.3 Replay attack protection with rolling counter 5.4.2.4 Convolution code for local or remote combining 5.4.2.5 Frame type, a multipurpose field 5.4.3 Downlink communication rules 5.4.3.1 Six steps to build a downlink radio burst 5.4.3.2 Object-triggered downlink communication 5.4.3.3 Relationship between uplink and downlink carrier center frequency 5.4.3.4 Downlink authentication reusing uplink context 5.5 Seven questions on Sigfox radio interface 5.5.1 Why Sigfox radio access network is not a cellular network? 5.5.2 Why is there no attachment procedure in Sigfox radio access network? 5.5.3 What is cooperative reception? 5.5.4 Why is there no destination address in Sigfox radio bursts? 5.5.5 Why does Sigfox radio access technology use ALOHA for accessing the spectrum? 5.5.6 Why is Sigfox radio access technology cognitive? 5.5.7 Why do Sigfox objects control the network and not the other way around? 5.6 Conclusion References 6 NB-IoT: concepts, applications, and deployment challenges 6.1 Narrowband-Internet of Things overview 6.1.1 History and standards 6.1.2 Narrowband-Internet of Things concepts 6.2 Narrowband-Internet of Things general features 6.2.1 Low power consumption 6.2.2 Wide coverage 6.2.3 High connection density 6.2.4 Privacy and reliability 6.3 Narrowband-Internet of Things fundamental theories and characteristics 6.3.1 Narrowband-Internet of Things key technologies 6.3.1.1 Signaling and data 6.3.1.2 Connection analysis 6.3.1.3 Latency analysis 6.3.1.4 Coverage enhancement 6.3.2 Narrowband-Internet of Things technical properties 6.3.2.1 Spectrum bandwidth and modulation 6.3.2.2 Operation mode 6.3.2.3 Transmission mode 6.3.2.4 Narrowband-Internet of Things frame structure 6.3.2.5 Narrowband-Internet of Things networking architecture 6.4 Narrowband-Internet of Things-related technologies 6.5 Narrowband-Internet of Things applications 6.5.1 Smart grid 6.5.2 Smart cities 6.5.3 Smart industry 6.6 Narrowband-Internet of Things deployment challenges and solutions 6.7 Conclusion References 7 Long-term evolution for machines (LTE-M) 7.1 Introduction 7.2 LTE-M as low-power wide-area network solution 7.2.1 LTE-M introduction 7.2.2 LTE-M objectives 7.3 LTE-M architecture 7.3.1 Modifications for LTE-M in 3GPP Release 13 7.3.2 Features for extended coverage 7.3.3 Power saving and extended battery life 7.3.4 Narrowband operation 7.3.5 Low cost and simplified operation 7.3.6 Use of LTE priority structure for LTE-M applications 7.4 Optimizing long-term evolution core network 7.5 LTE-M release sequence 13≥14≥15 7.6 LTE-M compatibility and migration 7.6.1 Migration from LTEto LTE-M 7.6.2 Coexistence of LTE-M and NB-IoT 7.6.3 Migration from long-term evolution machine to 5G 7.6.4 Private LTE-M networks 7.7 LTE-M use cases 7.7.1 Basic remote health monitoring 7.7.2 Advanced health monitoring and management 7.8 Concluding remarks Acronyms References 8 TV white spaces for low-power wide-area networks 8.1 Introduction 8.2 Architecture 8.2.1 Identification of TV white spaces 8.2.2 Architecture based on geolocation database 8.3 TV white spaces regulations and standards 8.4 TV white spaces protocols and technologies 8.4.1 TV white spaces identification protocols 8.4.2 TV white spaces network protocols 8.5 TV white spaces for low-power wide-area network 8.6 Applications 8.7 Challenges and opportunities References 9 Performance of LoRa technology: link-level and cell-level performance 9.1 Introduction 9.2 Related work 9.3 LoRa link-level behavior 9.3.1 LoRa modulation and demodulation 9.3.2 LoRa physical layer coding 9.3.3 Cochannel rejection 9.4 Analysis of cell capacity 9.4.1 Channel captures 9.4.2 Inter-spreading factor collisions 9.4.3 Model extension: nonuniform spreading factor allocation 9.5 Numerical results 9.5.1 Channel capture effects 9.5.2 Interfering spreading factors 9.5.3 Impact of fading 9.5.4 Nonuniform spreading factor allocation 9.6 Capacity with multiple gateways 9.7 Conclusion Acknowledgments References 10 Energy optimization in low-power wide area networks by using heuristic techniques 10.1 Introduction 10.2 Energy efficiency 10.3 Low-power wide area networks 10.4 Optimization techniques 10.4.1 Heuristics methods 10.4.2 Meta-heuristics methods 10.5 Classification of meta-heuristics methods 10.5.1 Genetic algorithms 10.5.2 Particle swarm optimization 10.5.3 Ant colony optimization algorithm 10.5.4 Tabu search 10.5.5 Simulated annealing algorithm 10.5.6 Artificial bee colony optimization 10.5.7 Gray wolf optimization 10.5.8 Memetic algorithms 10.5.9 Differential evolution algorithm 10.6 Adaptation of meta-heuristics techniques for energy optimization 10.6.1 Genetic algorithm 10.6.2 Simulated annealing algorithm 10.6.3 Particle swarm optimization 10.6.4 Ant colony optimization algorithm 10.6.5 Artificial bee colony 10.6.6 Gray wolf optimization 10.7 Performance analysis 10.7.1 Energy optimization with clustering mechanism 10.7.2 Energy optimization with routing mechanism 10.7.3 Energy optimization with virtual machine 10.7.4 Energy optimization in low-power wide area network 10.8 Conclusion References 11 Energy harvesting–enabled relaying networks 11.1 Introduction 11.2 State of the art 11.2.1 Scenario 1: Wireless power transfer constraint policies 11.2.2 Scenario 2: The impact of channel state information using HTPSR protocol 11.2.3 Scenario 3: The impact of hardware impairments on cognitive D2D communication 11.3 Performance analysis 11.3.1 Scenario 1: Wireless power transfer constraint policies 11.3.1.1 Separated power mode 11.3.1.2 Harvested power-assisted relay 11.3.2 Scenario 2: The impact of channel state information using HTPSR protocol 11.3.2.1 Calculation of the signal-to-noise ratio 11.3.2.1.1 Amplify-and-forward relaying 11.3.2.1.2 Decode-and-forward relaying 11.3.2.2 Delay-limited throughput 11.3.2.2.1 Amplify-and-forward relaying 11.3.2.2.2 Decode-and-forward relaying 11.3.2.2.3 Throughput analysis 11.3.2.3 Delay-tolerant transmission 11.3.2.3.1 Amplify-and-forward relaying 11.3.2.3.2 Decode-and-forward relaying 11.3.2.3.3 Throughput analysis 11.3.2.4 BER consideration 11.3.2.5 Optimization problems 11.3.2.5.1 Amplify-and-forward relaying 11.3.2.6 Decode-and-forward relaying 11.3.3 Scenario 3: The impact of hardware impairments on cognitive D2D communication 11.3.3.1 End-to-end signal-to-noise-plus-distortion ratio 11.3.3.1.1 Amplify-and-forward relaying 11.3.3.1.2 Decode-and-forward relaying 11.3.3.1.3 Peer-to-peer communication 11.3.3.2 Successful transmission probability 11.3.3.3 Average energy efficiency and average spectral efficiency 11.3.3.4 Optimization problem 11.4 Numerical results 11.4.1 Scenario 1: Wireless power transfer constraint policies 11.4.2 Scenario 2: The impact of channel state information using HTPSR protocol 11.4.3 Scenario 3: The impact of hardware impairments on cognitive D2D communication 11.5 Summary Acknowledgments References 12 Energy-efficient paging in cellular Internet of things networks 12.1 Introduction 12.2 Power saving solutions for cellular Internet of Things 12.2.1 Discontinuous reception 12.2.2 Discontinuous reception in connected mode 12.2.3 Discontinuous reception in idle mode 12.2.4 Extended discontinuous reception 12.2.5 Power saving mode 12.2.6 Wake up signal 12.3 Paging strategies 12.3.1 Standard paging 12.3.2 Group paging 12.3.3 Enhanced group paging 12.4 Applications for paging in cellular Internet of things 12.4.1 Group communications 12.4.2 Solutions for improving battery lifetime in Internet of things group communications 12.5 Paging enhancement in 5G 12.5.1 Secure paging 12.5.2 Random access network paging in 5G 12.6 Open issues and Third Generation Partnership Project study in Release 16 References 13 Guidelines and criteria for selecting the optimal low-power wide-area network technology 13.1 Introduction 13.1.1 Weightless 13.1.2 Ingenu-RPMA 13.1.3 Telensa 13.1.4 GSM-IoT 13.1.5 Wi-SUN 13.1.6 DASH7 13.1.7 IQRF 13.1.8 MIOTY 13.2 Technical factors 13.2.1 Physical layer 13.2.1.1 Frequency band 13.2.1.2 Modulation method 13.2.1.3 Data rate 13.2.1.4 Range 13.2.2 Link layer 13.2.2.1 MAC protocol 13.2.2.2 Bidirectionality 13.2.2.3 Packet size 13.2.3 Network layer 13.2.3.1 Network topology 13.2.3.2 Duty cycling 13.2.3.3 Scalability 13.2.3.4 Latency 13.2.4 Security 13.3 Implementation factors 13.3.1 Cost 13.3.1.1 Nodes and devices cost 13.3.1.2 Communication infrastructure cost 13.3.1.3 Data plans 13.3.2 Development 13.3.2.1 HW and SW tool kits 13.3.2.2 Documentation availability 13.3.2.3 Users and developers community 13.3.3 Status 13.3.3.1 Coverage/availability 13.3.3.2 Standards and alliances 13.3.3.3 Commercial devices 13.4 Functional factors 13.4.1 Energy consumption 13.4.2 Remote firmware updating 13.4.3 Location services 13.4.4 IP support 13.4.5 Network interoperability 13.5 Comparative analysis 13.5.1 Technical analysis 13.5.2 Implementation analysis 13.5.3 Functional analysis 13.5.4 Global analysis 13.6 Use-case examples 13.6.1 Agroindustry and forestry 13.6.2 Transport and logistics 13.6.3 Smart city 13.6.4 Infrastructure management 13.7 Conclusions References 14 Internet of wearable low-power wide-area network devices for health self-monitoring 14.1 Self-monitoring solutions, strategies, and risks 14.2 Low-power wide-area network technologies for wearable medical devices 14.3 Body-centric wireless smart sensors networks topologies 14.4 Low-power computing versus data accuracy for low-power wide-area network wearable devices 14.4.1 Low-power computing 14.4.2 Optimizing energy consumption 14.4.3 Data accuracy 14.5 Algorithms for efficient data processing by low-power wide-area networks 14.6 Future perspectives of the low-power wide-area network technologies for medical Internet of things 14.6.1 Network availability and localization 14.6.2 Resource management 14.6.3 Security and privacy management 14.6.4 Support a considerable number of devices 14.6.5 Interference mitigation 14.6.6 Hardware complexity 14.7 Conclusions Acknowledgments References 15 LoRaWAN for smart cities: experimental study in a campus deployment 15.1 Introduction 15.2 LoRa, radio, and network 15.2.1 LoRa modulation basics 15.2.1.1 Bit rates 15.2.1.2 Packet air time 15.2.2 Long-range wide-area network protocol 15.2.2.1 Long-range wide-area network nodes 15.2.2.2 Long-range wide-area network channel management 15.2.2.3 Long-range wide-area network gateway 15.2.2.4 Packet encoding with Protobuf 15.2.2.5 LoRa network server 15.3 Performance in real-world long-range wide-area network deployment scenarios 15.3.1 Campus-wide long-range wide-area network deployment 15.3.1.1 Experimental setup 15.3.1.2 Measurements on SF7 15.3.1.3 Measurements on SF12 15.3.1.4 Range and packet error rate for SF8–SF11 15.3.1.5 Path loss estimation 15.3.1.6 Campus deployment: key observations 15.3.2 Note on scalability and drawbacks of long-range wide-area network under dense foliage scenario 15.3.3 Other global long-range wide-area network deployments 15.3.3.1 Bologna, Italy 15.3.3.2 Paris, France 15.3.3.3 Bangkok, Thailand 15.3.3.4 Lille, France 15.4 Internet of things middleware for smart cities 15.4.1 Aspects in Internet of things network deployments 15.4.2 Long-range wide-range area network operation and management 15.4.3 Configurable parameters 15.4.4 Network management 15.5 Summary References 16 Exploiting LoRa, edge, and fog computing for traffic monitoring in smart cities 16.1 Introduction 16.2 Related work 16.3 Edge and fog computing 16.3.1 Edge AI: artificial intelligence at the edge of the network 16.4 Low-power wide-area network technology 16.4.1 LoRa for the physical layer 16.4.2 Long-range wide-area network 16.4.3 Symphony Link 16.4.4 MoT: MAC on time 16.5 System architecture 16.5.1 Device layer 16.5.2 Edge layer 16.5.3 Fog layer 16.5.4 Cloud layer 16.5.5 Terminal layer 16.6 LoRa and mobile edge computing: a use case for traffic monitoring 16.6.1 Performance evaluation 16.7 Discussion 16.8 Conclusion References 17 Security in low-power wide-area networks: state-of-the-art and development toward the 5G 17.1 Introduction 17.1.1 Low-power wide-area architecture 17.1.2 Low-power wide-area technology—security and challenges 17.2 Security features of state-of-the-art low-power wide-area technologies 17.2.1 Sigfox 17.2.2 Long-range wide-area network 17.2.3 Narrowband-Internet of Things 17.3 Future vision: Internet of things and 5G core network—security overview Acknowledgments References 18 Hardware and software platforms for low-power wide-area networks 18.1 Introduction 18.2 Hardware platforms 18.2.1 Pycom platform 18.2.2 Lite gateways 18.2.3 iM880B-L 18.2.4 Remote eye platform 18.2.5 Arm Cordio-N Internet protocol for narrowband-Internet of things 18.2.6 CableLabs LoRa server 18.2.7 Libelium 18.2.8 The Things Uno and Nodes 18.2.9 Mainflux 18.2.10 Silabs STK3400 Happy Gecko board 18.2.11 OpenMote 18.2.12 BigClown 18.2.13 Arduino-based platforms 18.2.13.1 Arduino MKR WAN 1300 18.2.13.2 WiMOD Shield for Arduino 18.2.13.3 Seeeduino LoRaWAN 18.2.14 KRATOS 18.2.15 Low-power wide-area network universal serial bus dongle 18.2.15.1 Long-range wide-area network universal serial bus dongle 18.2.15.2 LoStik universal serial bus dongle 18.2.15.3 LD-20 LoRa universal serial bus dongle 18.2.16 Universal software radio peripheral 18.3 Software platforms 18.3.1 CupCarbon 18.3.2 LoRaSim and extended LoRaSim 18.3.3 Other simulators 18.3.4 The Things Network 18.3.5 GNU Radio References Index