Reconfigurable Intelligent Surfaces (RIS) Global Market 2025-2035

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Published: November 2024
Pages: 176
Tables: 98
Figures: 46

Reconfigurable Intelligent Surfaces (RIS), also known as Intelligent Reflecting Surfaces (IRS) or software-controlled metasurfaces, are artificial structures composed of a large number of small, passive elements that can be electronically controlled to manipulate electromagnetic waves. These surfaces can reflect, refract, absorb, or focus incoming signals in desired directions, effectively shaping the wireless propagation environment. Due to recent advances in metamaterials, Reconfigurable Intelligent Surface (RIS) has emerged as a promising technology for future 6G wireless communications. Benefiting from its high array gain, low cost, and low power consumption, RISs are expected to greatly enlarge signal coverage, improve system capacity, and increase energy efficiency.

RIS technology offers revolutionary capabilities in manipulating electromagnetic waves, enabling enhanced coverage, capacity, and energy efficiency in wireless networks. As 5G networks expand and 6G development accelerates, RIS is expected to play a crucial role in overcoming current limitations in wireless communications. Key applications span telecommunications, smart cities, Industrial IoT, healthcare, automotive, aerospace, and consumer electronics. The market is driven by increasing demand for high-speed, low-latency communications, growth in IoT adoption, and the need for energy-efficient wireless solutions. However, challenges include high initial costs, technical complexities in large-scale deployment, and standardization issues.

Report contents include:

Market Size and Growth Projections: Detailed forecasts of the RIS market size and growth rate from 2025 to 2035, segmented by technology type, application, and geography.
Technology Deep Dive: Comprehensive analysis of various RIS technologies, including metasurfaces, liquid crystal-based RIS, MEMS-based RIS, and emerging approaches.
Analysis of Transparent and Non-Transparent Reflectors.
Application Landscape: Exploration of key application areas such as 5G/6G networks, IoT, smart cities, autonomous vehicles, and aerospace communications.
Competitive Landscape: Profiles of leading companies and emerging players in the RIS space, including their technologies, strategies, and market positioning. Companies profiled include Alcan Systems, Alphacore Inc., Edgehog Advanced Technologies, Evolv Technologies Inc., Fractal Antenna Systems Inc., Greenerwave, Huawei, Kymeta Corporation, Leadoptik Inc., Lumotive, META, Metaboards Limited, Metawave Corporation, Nokia, NTT DOCOMO, Pivotal Commware Inc., SK Telecom, Teraview Limited, and ZTE Corporation.
Future Outlook: Assessment of emerging trends, potential disruptions, and long-term prospects for RIS technology.
Developments in RIS technology, including:
- Integration with AI and machine learning for adaptive control
- Quantum RIS concepts pushing the boundaries of performance
- Self-configuring and self-healing RIS for enhanced reliability
- Holographic radio and terahertz communications enabled by RIS
Market Drivers and Opportunities
Challenges and Market Dynamics
Technology Benchmarking and Performance Analysis
Comprehensive comparison of different RIS technologies.
Integration with Wireless Communication Systems.
Environmental and Sustainability Considerations.
Standardization and Regulatory Landscape.

1 EXECUTIVE SUMMARY 15

1.1 Overview of Reconfigurable Intelligent Surfaces (RIS) 15
1.2 Key Market Drivers and Challenges 16
1.3 Technology and Market Trends 16
1.4 Metamaterials key to RIS 17
1.5 Market Size and Growth Projections 18
1.6 Competitive Landscape Overview 18
1.7 Future Outlook and Opportunities 19

2 INTRODUCTION 20

2.1 Technology overview 20
- 2.1.1 Key features and functionality 23
- 2.1.2 Frequencies 24
- 2.1.3 Physics of Electromagnetic Wave Manipulation 26
  - 2.1.3.1 Reflection 27
  - 2.1.3.2 Refraction 28
  - 2.1.3.3 Diffraction 28
  - 2.1.3.4 Absorption 28
- 2.1.4 RIS Operating Principles 29
  - 2.1.4.1 Passive RIS 30
  - 2.1.4.2 Active RIS 30
  - 2.1.4.3 Hybrid RIS 31
- 2.1.5 Key Performance Parameters 31
  - 2.1.5.1 Reflection Coefficient 31
  - 2.1.5.2 Phase Shift Range 31
  - 2.1.5.3 Bandwidth 32
  - 2.1.5.4 Power Consumption 32
  - 2.1.5.5 Reconfiguration Speed 33
- 2.1.6 Design Considerations for RIS 33
  - 2.1.6.1 Surface Element Design 33
  - 2.1.6.2 Array Configuration 34
  - 2.1.6.3 Control Mechanisms 34
  - 2.1.6.4 Integration with Existing Infrastructure 35
2.2 System Architecture 35
2.3 Importance in Modern Wireless Communications 36
2.4 Advantages Over Traditional Wireless Technologies 37
2.5 Current Limitations and Challenges 39
2.6 Comparison with Other Smart Electromagnetic (EM) Devices 42

3 RIS TECHNOLOGIES 43

3.1 Transparent vs. Non-Transparent Reflectors 43
- 3.1.1 Transparent Reflectors 44
- 3.1.2 Non-Transparent Reflectors 45
- 3.1.3 By company 45
3.2 Metasurfaces 46
- 3.2.1 Principles of Metasurfaces 46
- 3.2.2 Types of Metasurfaces 47
  - 3.2.2.1 Meta-Lens 48
  - 3.2.2.2 Metasurface holograms 48
  - 3.2.2.3 Flexible metasurfaces 49
- 3.2.3 Fabrication Techniques 49
- 3.2.4 Characteristics 50
3.3 Liquid Crystal-based RIS 50
- 3.3.1 Operating Principles 50
- 3.3.2 Advantages and Limitations 51
3.4 MEMS-based RIS 52
- 3.4.1 MEMS Technology Overview 52
- 3.4.2 Design and Fabrication 52
- 3.4.3 Performance Metrics 53
3.5 Varactor Diode-based RIS 53
- 3.5.1 Overview 53
3.6 PIN Diode-based RIS 54
- 3.6.1 Overview 54
3.7 Other Materials 56
- 3.7.1 Ferroelectric materials 56
- 3.7.2 Phase Change Materials 57
- 3.7.3 Graphene 58
3.8 Comparison of RIS Technologies 59
- 3.8.1 Performance Metrics 59
- 3.8.2 Cost Analysis 59
- 3.8.3 Scalability and Manufacturing Considerations 59

4 RIS IN WIRELESS COMMUNICATION SYSTEMS 61

4.1 5G 61
- 4.1.1 Overview 61
- 4.1.2 Market drivers 61
  - 4.1.2.1 Coverage Enhancement Needs 62
  - 4.1.2.2 Energy Efficiency Requirements 62
  - 4.1.2.3 Capacity Improvement Demands 63
  - 4.1.2.4 Cost Optimization Goals 63
- 4.1.3 Applications 64
- 4.1.4 RIS operation phases 64
- 4.1.5 Functionalities of RIS 65
- 4.1.6 RIS prototypes 65
- 4.1.7 5G Network Requirements 67
- 4.1.8 RIS Role in 5G Infrastructure 68
- 4.1.9 Integration with 5G Networks 68
  - 4.1.9.1 Network Integration Strategies 69
  - 4.1.9.2 Channel Modeling 71
  - 4.1.9.3 Signal Processing 72
  - 4.1.9.4 Integration Challenges and Solutions 73
- 4.1.10 Performance Enhancement 74
  - 4.1.10.1 Coverage Optimization 74
  - 4.1.10.2 Capacity Enhancement 75
  - 4.1.10.3 Energy Efficiency 77
- 4.1.11 Advanced Applications 80
  - 4.1.11.1 mmWave Communications 80
  - 4.1.11.2 Massive MIMO Systems 82
  - 4.1.11.3 IoT Applications 84
- 4.1.12 Implementation Challenges 86
  - 4.1.12.1 Technical Challenges 86
  - 4.1.12.2 Standardization 87
- 4.1.13 Future Directions 89
  - 4.1.13.1 Hardware Advancements 89
  - 4.1.13.2 Control Systems 89
  - 4.1.13.3 Integration Capabilities 90
  - 4.1.13.4 Performance Enhancement 90
- 4.1.14 Market and technology roadmap 90
4.2 6G and Beyond 91
- 4.2.1 6G Reconfigurable intelligent surfaces and metamaterials opportunities 91
- 4.2.2 RIS materials applications 94
- 4.2.3 RIS costs in volume 94
- 4.2.4 RIS formulations 94
- 4.2.5 RIS in Terahertz Communications 95
- 4.2.6 Holographic Radio 95
- 4.2.7 Intelligent Reflecting Surfaces for Satellite Communications 95
4.3 MIMO Systems and RIS 96
- 4.3.1 RIS-assisted MIMO 96
- 4.3.2 RIS-based Massive MIMO 97
- 4.3.3 Performance Enhancements and Challenges 98
4.4 Beamforming and RIS 98
- 4.4.1 Passive Beamforming 99
- 4.4.2 Hybrid Beamforming with RIS 99
- 4.4.3 Adaptive Beamforming Techniques 100
4.5 Energy Efficiency in Wireless Networks 100
- 4.5.1 RIS for Green Communications 101
- 4.5.2 Energy Harvesting with RIS 101

5 MARKETS AND APPLICATIONS 103

5.1 Telecommunications 103
- 5.1.1 Coverage Enhancement 104
- 5.1.2 Capacity Improvement 104
- 5.1.3 Interference Mitigation 105
- 5.1.4 Market forecast 105
5.2 Smart Cities and IoT 106
- 5.2.1 Urban Environment Monitoring 107
- 5.2.2 Smart Transportation Systems 107
- 5.2.3 Energy Management in Buildings 108
- 5.2.4 Market forecast 108
5.3 Industrial IoT and Industry 4.0 110
- 5.3.1 Factory Automation 110
- 5.3.2 Warehouse Management 110
- 5.3.3 Process Control and Monitoring 111
- 5.3.4 Market forecast 112
5.4 Healthcare and Medical Applications 114
- 5.4.1 Wireless Body Area Networks 114
- 5.4.2 Remote Patient Monitoring 114
- 5.4.3 Medical Imaging Enhancement 115
- 5.4.4 Market forecast 115
5.5 Automotive and Transportation 116
- 5.5.1 Vehicle-to-Everything (V2X) Communications 116
- 5.5.2 Autonomous Vehicles 117
- 5.5.3 Intelligent Transportation Systems 117
- 5.5.4 Market forecast (IoT) 117
5.6 Aerospace and Defense 119
- 5.6.1 Radar Systems Enhancement 119
- 5.6.2 Secure Communications 119
- 5.6.3 Stealth Technology 120
- 5.6.4 UAVs 121
5.7 Smart Home and Consumer Electronics 121
- 5.7.1 In-home Wireless Coverage Optimization 122
- 5.7.2 Device-to-Device Communications 122
- 5.7.3 Augmented and Virtual Reality Applications 122

6 MARKET ANALYSIS AND TRENDS 124

6.1 Global Market Size and Growth Projections 124
- 6.1.1 Market Segmentation by Technology 124
- 6.1.2 Market Segmentation by Market 125
- 6.1.3 Market Segmentation by Geography 126
6.2 Key Market Drivers 127
- 6.2.1 Increasing Demand for High-Speed, Low-Latency Communications 127
- 6.2.2 Growth in IoT and Smart Device Adoption 127
- 6.2.3 Advancements in 5G and 6G Technologies 127
- 6.2.4 Need for Energy-Efficient Wireless Solutions 127
- 6.2.5 Other drivers 127
6.3 Market Challenges and Barriers 128
- 6.3.1 High Initial Implementation Costs 128
- 6.3.2 Technical Complexities in Large-Scale Deployment 128
- 6.3.3 Standardization and Interoperability Issues 128
- 6.3.4 Regulatory and Compliance Challenges 129
- 6.3.5 Other challenges and barriers 129
6.4 Emerging Market Opportunities 130
- 6.4.1 Integration with Edge Computing 130
- 6.4.2 RIS for Satellite and Space Communications 131
- 6.4.3 Advanced Materials for RIS 131
- 6.4.4 AI and Machine Learning Integration 131
- 6.4.5 Quantum RIS Concepts 132
- 6.4.6 Cognitive RIS 132
- 6.4.7 Self-configuring and Self-healing RIS 133
- 6.4.8 Integration with Blockchain for Secure Communications 133
6.5 Future Outlook 134
- 6.5.1 RIS in 6G and Beyond 134
- 6.5.2 Holographic Communications 134
- 6.5.3 Space-based RIS Networks 134
- 6.5.4 AI and Machine Learning in RIS Control 134
- 6.5.5 RIS for Terahertz and Optical Wireless Communications 135
- 6.5.6 Biological and Health Implications of Large-Scale RIS Deployment 135

7 STANDARDIZATION AND REGULATORY ENVIRONMENT 137

7.1 Current Standards Related to RIS 137
- 7.1.1 IEEE Standards 137
- 7.1.2 3GPP Specifications 137
- 7.1.3 ETSI Standards 137
7.2 Spectrum Allocation and Management 138
- 7.2.1 Safety and Electromagnetic Compatibility Regulations 138
- 7.2.2 Data Privacy and Security Considerations 138

8 ENVIRONMENTAL AND SUSTAINABILITY CONSIDERATIONS 140

8.1 Energy Efficiency of RIS-enabled Networks 140
8.2 Life Cycle Assessment of RIS Technologies 140
8.3 E-waste Management and Recycling 141
8.4 Sustainable Manufacturing Practices 141
8.5 RIS Role in Smart Grid and Energy Management 142
8.6 Environmental Impact of Large-Scale RIS Deployment 142

9 CHALLENGES AND LIMITATIONS 144

9.1 Technical Challenges in RIS Implementation 144
9.2 Scaling Up Production and Cost Reduction 144
9.3 Integration with Existing Infrastructure 145
9.4 Performance in Complex Environments 146
9.5 Security and Privacy Concerns 146

10 COMPANY PROFILES 148 (20 company profiles)

11 APPENDICES 169

11.1 Glossary of Terms 169
11.2 List of Abbreviations 170
11.3 Research Methodology 171

12 REFERENCES 172

List of Tables

Table 1. Key Market Drivers and Challenges in RIS. 16
Table 2. Reconfigurable Intelligent Surfaces (RIS) Technology and Market Trends 17
Table 3. Future Outlook and Opportunities in RIS. 19
Table 4. Overview of different RIS types. 22
Table 5. RIS operation phases. 23
Table 6. RIS Hardware. 24
Table 7. Comparison of different RIS techniques. 24
Table 8. RIS functionalities. 25
Table 9. Challenges for fully functionalized RIS environments. 25
Table 10. Comparison of Reflection Coefficient Across Different RIS Technologies. 28
Table 11. Benchmarking of Reconfigurable Intelligent Surfaces (RIS) types. 29
Table 12. Comparison of Key Performance Metrics for Different RIS Technologies. 31
Table 13.Comparison of Phase Shift Range Across Different RIS Technologies. 32
Table 14. Bandwidth and Frequency Ranges for Various RIS Technologies. 32
Table 15. Power Consumption Comparison of RIS Technologies. 32
Table 16. Energy Efficiency Comparison: RIS-enabled vs. Traditional Wireless Networks. 33
Table 17. Reconfiguration Speed Comparison Across Different RIS Types. 33
Table 18. Integration Considerations. 35
Table 19. Advantages Over Traditional Wireless Technologies. 38
Table 20. Current Limitations and Challenges. 39
Table 21. RIS vs Other Smart Electromagnetic (EM) Devices. 42
Table 22. Types of RIS by transparency. 43
Table 23. Comparative Analysis of Transparent vs. Non-Transparent Reflectors in RIS. 44
Table 24. Transparency/Non-Transparency Categorization by company 45
Table 25.Types of Metasurfaces. 47
Table 26. Metasurface fabrication techniques. 50
Table 27. Distinguishing between conductive and optical metamaterials. 50
Table 28. Advantages and Limitations of Liquid Crystal-based RIS. 51
Table 29. MEMS-based RIS Technology Performance Metrics. 53
Table 30. Comparison of RIS Performance in Different Environmental Conditions. 59
Table 31. Cost Analysis. 59
Table 32. Market drivers for reconfigurable intelligent surfaces in 5G. 61
Table 33. Coverage Enhancement Metrics. 62
Table 34. Energy Efficiency Metrics. 62
Table 35. Cost Optimization Metrics. 63
Table 36. Reconfigurable intelligent surface (RIS) - applications in 5G. 64
Table 37. RIS operation phases. 64
Table 38. Functionalities of RIS 65
Table 39. RIS 5G Prototypes. 66
Table 40. 5G Network Requirements. 67
Table 41. RIS applications in wireless networks. 68
Table 42. Network integration strategies for RIS technology . 69
Table 43. Integration with Existing Infrastructure. 70
Table 44. Performance Metrics in 5G Network Integration. 70
Table 45. Path Loss Models. 71
Table 46. Channel Estimation Techniques. 71
Table 47. Multi-user Scenarios. 71
Table 48. Precoding Techniques. 73
Table 49. Integration Challenges and Solutions. 73
Table 50. Coverage Extension Methods. 74
Table 51. Indoor Coverage Solutions. 75
Table 52. Capacity Enhancement. 75
Table 53. Energy Efficiency. 77
Table 54. Power Consumption Analysis. 78
Table 55. High-Frequency Challenges. 81
Table 56. RIS Solutions for mmWave. 81
Table 57. Performance Analysis. 82
Table 58. Implementation Challenges. 84
Table 59. Technical Challenges for RIS. 86
Table 60. Hardware Limitations for RIS in 5G. 86
Table 61. Standardization Challenges. 87
Table 62. RIS Materials Applications. 94
Table 63. RIS costs in volume. 94
Table 64. RIS formulations. 94
Table 65. Adaptive Beamforming Techniques. 100
Table 66. Global market forecast for RIS Adoption in 5G/6G Networks (2025-2035), Millions USD. 105
Table 67. Urban Environment Monitoring Applications. 107
Table 68. Smart Transportation Applications. 107
Table 69. Energy Management Applications. 108
Table 70. Global market forecast for RIS Adoption in Smart Cities and IoT (2025-2035), Millions USD. 108
Table 71.Industrial IoT Applications. 110
Table 72. Process Control Applications. 111
Table 73. Global market forecast for RIS Adoption in Industrial IoT and Industry 4.0 Applications (2025-2035), Millions USD. 112
Table 74. Wireless Body Area Networks Applications. 114
Table 75. Remote Patient Monitoring Applications. 114
Table 76. Global Market Forecast for RIS Adoption in Healthcare/Medical (2025-2035), Millions USD. 115
Table 77.Automotive and Transportation Applications. 116
Table 78. Global market forecast for RIS Adoption in Automotive and Transportation (2025-2035), Millions USD 117
Table 79. Augmented and Virtual Reality Applications. 122
Table 80. Global RIS Market Size, by Technology Type, 2025-2035 (USD Million). 124
Table 81. Global RIS Market Size, by market, 2025-2035 (USD Million). 125
Table 82. Global RIS Market Size, by Region, 2025-2035 (USD Million). 126
Table 83. Applications in Satellite and Space Communications. 131
Table 84.RIS Material Types and Applications. 131
Table 85. Quantum RIS Concepts. 132
Table 86. Biological and Health Implications. 136
Table 87. Safety and Electromagnetic Compatibility Regulations. 138
Table 88. Data Privacy and Security Considerations. 138
Table 89. Environmental Impact Comparison: RIS vs. Traditional Wireless Infrastructure. 140
Table 90. Energy Efficiency Metrics. 140
Table 91. Life Cycle Assessment of RIS Technologies. 140
Table 92. E-waste Management and Recycling. 141
Table 93. Sustainable Manufacturing for RIS Technology. 142
Table 94. Smart Grid Integration. 142
Table 95. Environmental Impact of Large-Scale RIS Deployment. 143
Table 96. Technical Challenges in RIS Implementation. 144
Table 97. Glossary of Terms. 169
Table 98. List of Abbreviations. 170

List of Figures

Figure 1. A typical use case of an RIS, where it receives a signal from the transmitter and re-radiates it focused on the receiver. 15
Figure 2. Basic RIS application: coverage extension in a cellular network. 20
Figure 3. Comparison of different wireless systems. 21
Figure 4. Schematic Diagram of a Typical RIS Structure. 22
Figure 5. Intelligent reflection and refraction. 27
Figure 6. Hardware architecture of RIS. 36
Figure 7. Scanning electron microscope (SEM) images of several metalens antenna forms. 48
Figure 8. Transparent and flexible metamaterial film developed by Sekishi Chemical. 49
Figure 9. The structure of a three-layered PIN diode based 2-bit RIS panel. 55
Figure 10. NTT DOCOMO transparent RIS. 66
Figure 11. Meta Nanoweb® . 66
Figure 12. RIS mmWave communication. 81
Figure 13. RIS in 5G Market and technology roadmap. 91
Figure 14. Comparison between 5G and 6G wireless systems in terms of key-performance indicators. 91
Figure 15. RIS-assisted wireless communication. 93
Figure 16. RIS-enabled, self-sufficient ultra-massive 6G UM-MIMO base station design. 96
Figure 17. Active and passive beamforming in RIS-assisted cell-free massive MIMO. 97
Figure 18. Lumotive advanced beam steering concept. 98
Figure 19. Deployment of RIS in a building for communication. 103
Figure 20. RIS-assisted indoor enhancement of outdoor macro station coverage. 104
Figure 21. Global market forecast for RIS Adoption in 5G/6G Networks (2025-2035), Millions USD. 106
Figure 22. Global market forecast for RIS Adoption in Smart Cities and IoT (2025-2035), Millions USD. 109
Figure 23. RIS-aided IoT communication. 111
Figure 24. Global market forecast for RIS Adoption in IoT Applications (2025-2035), Millions USD. 113
Figure 25. Global Market Forecast for RIS Adoption in Healthcare/Medical (2025-2035), Millions USD. 115
Figure 26. RIS-assisted V2V communication system. 117
Figure 27. RIS vehicle network communication. 117
Figure 28. Global market forecast for RIS Adoption in Automotive and Transportation (2025-2035), Millions USD. 118
Figure 29. PHY-Layer security issue scheme of RIS. 120
Figure 30. RIS UAV communication. 121
Figure 31. RIS VLC in a smart office room. 122
Figure 32. Global RIS Market Size, by Technology Type, 2025-2035 (USD Million). 124
Figure 33. Global RIS Market Size, by Application, 2025-2035 (USD Million). 125
Figure 34. Global RIS Market Size, by Region, 2025-2035 (USD Million). 126
Figure 35. RIS-enabled wireless edge computing. 130
Figure 36. Edgehog Advanced Technologies Omnidirectional anti-reflective coating. 149
Figure 37. FM/R technology. 152
Figure 38. Metablade antenna. 152
Figure 39. MTenna flat panel antenna. 155
Figure 40. Kymeta u8 antenna installed on a vehicle. 156
Figure 41. LIDAR system for autonomous vehicles. 158
Figure 42. Light-control metasurface beam-steering chips. 159
Figure 43. Metaboard wireless charger. 160
Figure 44. Metalenz metasurface-based optics on a chip. 162
Figure 45. NTT DOCOMO transparent RIS. 165
Figure 46. ZTE dynamic reconfigurable intelligent surface 2.0 product. 168

The Global Market for Reconfigurable Intelligent Surfaces (RIS) 2025-2035

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