Why RIS Applications are Broad
RIS is not a single application. It is a platform technology. Once a surface can shape radio propagation, it can help many wireless tasks: stronger links, lower interference, better localization, improved sensing, and energy-aware coverage.
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
1. Coverage Extension
The most intuitive use is coverage recovery. If a direct path is blocked, an RIS can create a reflected path. This is especially useful at mmWave and sub-THz frequencies, where blockage is severe.
Examples:
- Indoor dead-zone coverage.
- Urban street-canyon links.
- Factory-floor robot connectivity.
- Cell-edge improvement.
Coverage map: what one RIS adds
1. Formula and symbols
- : sum of modeled path powers at a map cell (incoherent addition)
- : receiver noise
- : target SNR
- : valid street cells
Coverage is the fraction meeting the target, with each RIS re-aimed at each evaluated point.
2. Work with the current inputs
3. Result
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
2. Interference Mitigation
RIS can be configured so reflected interference arrives out of phase with direct interference. It can also steer the desired signal away from unintended receivers.
This does not mean interference disappears everywhere. It means the surface can shape the spatial distribution of energy at selected locations.
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
3. Physical Layer Security
Wireless signals naturally leak. RIS can improve secrecy by:
- Increasing signal strength at the legitimate user.
- Creating weak-signal zones near eavesdroppers.
- Randomizing or shaping propagation paths.
This is particularly attractive when combined with beamforming and artificial noise.
Physical-layer security: aim at Bob, starve Eve
1. Formula and symbols
- : Linear receive SNR at Bob
- : Linear receive SNR at Eve
- : illustrative secrecy rate in bit/s/Hz
[x]₊ = max(x,0)
Both SNRs come from the same phase-only beam pattern.
2. Work with the current inputs
3. Result
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
4. Localization and Positioning
RIS can act as a known virtual anchor. If the receiver knows the RIS location and estimates the reflected path delay/angle, it can infer position even when the direct path is blocked.
This is one of the strongest research directions for RIS because 6G aims for high-accuracy positioning as a native service.
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
5. Smart Indoor Environments
RIS panels can be placed on walls or ceilings in:
- Hospitals.
- Factories.
- Airports.
- Lecture halls.
- Laboratories.
The goal is to make indoor propagation more predictable. Instead of relying on random wall reflections, the building actively assists communication.
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
6. Wireless Power and Battery-Free IoT
RIS can focus RF energy toward low-power sensors. The energy levels are usually small, but for ultra-low-power IoT nodes, even small improvements can matter.
The practical challenge is that information transfer and power transfer may require different beam patterns.
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
7. Sensing and Environmental Awareness
RIS can help radio sensing by illuminating hidden targets, enhancing weak echoes, or providing an additional geometric viewpoint. This connects directly to RIS-assisted ISAC.
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
Application Selection Guide
| Problem | RIS role |
|---|---|
| Blocked user | Create virtual LoS |
| Strong interference | Create spatial nulls or redirect energy |
| Weak localization geometry | Add virtual anchor |
| Indoor mmWave coverage | Smart wall/ceiling reflection |
| Low-power sensor | Focus RF energy |
| Hidden target sensing | Provide NLoS illumination path |
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
Takeaway
- When to consider RIS: a controllable reflected path is more practical than another active site.
- Typical tasks: blocked high-frequency coverage, localization, and joint communication/sensing.
- Compare fairly: include RIS control overhead and the no-RIS baseline.
References for this section3
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.
Check your understanding
0 of 4 answered
In the coverage map, why does the shadow behind the building improve with an RIS?
What does placing a null toward Eve do to the secrecy rate?
Which application uses the RIS as a known geometric reference?
Why is RIS-assisted wireless power transfer limited?
Complete references and further reading
- E. Basar et al., "Wireless Communications Through Reconfigurable Intelligent Surfaces", IEEE Access, 2019.
- Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
- K. M. Faisal and W. Choi, "Machine Learning Approaches for Reconfigurable Intelligent Surfaces: A Survey", IEEE Access, vol. 10, pp. 27343-27367, 2022.