6. RIS in 6G mmWave Networks

RIS as 6G Infrastructure

6G is expected to move beyond only connecting users. It will also localize, sense, compute, and adapt. RIS fits this vision because it lets the network program parts of the physical environment.

In a mature 6G deployment, RIS panels may be installed on:

• Building facades.
• Street furniture.
• Factory walls.
• Indoor ceilings.
• Vehicles and UAVs.
• Smart windows.

References for this section3

• Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
• M. Di Renzo et al., "Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces", IEEE JSAC, 2020.
• A. Tishchenko et al., "The Emergence of Multi-Functional and Hybrid Reconfigurable Intelligent Surfaces for Integrated Sensing and Communications: A Survey", IEEE Communications Surveys & Tutorials, early access, 2025.

Network-Level View

RIS control is not only an electromagnetic problem. It is also a network-management problem involving scheduling, mobility, control signaling, and AI.

The RIS control loop

1. Formula and symbols

$$f_D=vf_c/c,\quad T_c\approx0.423/f_D,\quad T_{\rm loop}\leq T_c$$

• $v$: speed in m/s
• $f_c$: carrier in Hz
• $c$: wave speed
• $f_D$: maximum Doppler
• $T_c$: coherence estimate
• $T_{\rm loop}$: chosen update period

The inequality is a freshness heuristic, not a tracking guarantee.

User speed

30 km/h

Loop period

5 ms

2. Work with the current inputs

$$v=30/3.6\ \mathrm{m/s},\quad f_D=\frac{(30/3.6)28\times10^9}{299792458}\ \mathrm{Hz}$$

$$T_c=0.54\ \mathrm{ms},\quad T_{\rm loop}=5\ \mathrm{ms}$$

3. Result

Coherence time0.54 msat 28 GHz

Loop period5 ms

Keeps up?Nothe RIS lags the channel

References for this section3

• Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
• M. Di Renzo et al., "Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces", IEEE JSAC, 2020.
• A. Tishchenko et al., "The Emergence of Multi-Functional and Hybrid Reconfigurable Intelligent Surfaces for Integrated Sensing and Communications: A Survey", IEEE Communications Surveys & Tutorials, early access, 2025.

Why mmWave and sub-THz Need RIS

mmWave/sub-THz systems offer large bandwidth, but links are easily blocked. RIS helps by:

• Creating reflected backup paths.
• Improving cell-edge coverage.
• Supporting directional beam discovery.
• Helping localization and sensing.
• Reducing the need for many active small cells.

Coverage map: adding RIS panels

1. Formula and symbols

$$\gamma_{\rm dB}=P_{r,\rm dBm}-N_{\rm dBm}$$

$$q_{\rm covered}=\frac{\#\{i:\gamma_i\geq\gamma_{\rm min}\}}{N_{\rm valid}}$$

• $P_r$: sum of modeled path powers at a map cell (incoherent addition)
• $N$: receiver noise
• $\gamma_{\min}$: target SNR
• $N_{\rm valid}$: valid street cells

Coverage is the fraction meeting the target, with each RIS re-aimed at each evaluated point.

RIS panels on the facade

0 panels1 panel2 panels3 panels

Carrier

28 GHz100 GHz

Elements per panel

1,0244,09616,384

Target SNR

15 dB

2. Work with the current inputs

$$q_{\rm covered}=\frac{4576}{6190}=0.7393$$

$$\Delta q=100(0.7393-0.4511)=28.8\ \text{percentage points}$$

3. Result

Area covered74%SNR ≥ 15 dB

Without any RIS45%

Gained by RIS+29 points

Hovered point—move over the map

References for this section3

• Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
• M. Di Renzo et al., "Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces", IEEE JSAC, 2020.
• A. Tishchenko et al., "The Emergence of Multi-Functional and Hybrid Reconfigurable Intelligent Surfaces for Integrated Sensing and Communications: A Survey", IEEE Communications Surveys & Tutorials, early access, 2025.

AI and Digital Twins

Large RIS networks cannot be optimized by slow exhaustive search. AI can help learn:

• Which RIS panels should be active.
• Which phase patterns work in a given environment.
• How mobility affects the best configuration.
• How sensing information predicts future beams.

Digital twins can provide simulated environments for training and planning. The digital twin stores geometry, materials, RIS locations, and traffic patterns, then predicts good radio configurations.

References for this section3

• Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
• M. Di Renzo et al., "Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces", IEEE JSAC, 2020.
• A. Tishchenko et al., "The Emergence of Multi-Functional and Hybrid Reconfigurable Intelligent Surfaces for Integrated Sensing and Communications: A Survey", IEEE Communications Surveys & Tutorials, early access, 2025.

Deployment Challenges

• Backhaul/control: RIS controllers need reliable commands.
• Calibration: Real RIS responses differ from ideal models.
• Standardization: RIS needs interfaces for control, measurement, and reporting.
• Maintenance: Outdoor surfaces face weather, aging, and hardware failures.
• Security: Malicious RIS control could redirect or jam links.

References for this section3

• Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
• M. Di Renzo et al., "Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces", IEEE JSAC, 2020.
• A. Tishchenko et al., "The Emergence of Multi-Functional and Hybrid Reconfigurable Intelligent Surfaces for Integrated Sensing and Communications: A Survey", IEEE Communications Surveys & Tutorials, early access, 2025.

Research Directions

• Multi-RIS coordination.
• Active/STAR/multifunctional RIS.
• Near-field RIS for 6G.
• RIS-aided ISAC.
• Learning-based RIS beam management.
• Hardware-aware channel modeling.
• Experimental validation with real prototypes.

References for this section3

• Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
• M. Di Renzo et al., "Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces", IEEE JSAC, 2020.
• A. Tishchenko et al., "The Emergence of Multi-Functional and Hybrid Reconfigurable Intelligent Surfaces for Integrated Sensing and Communications: A Survey", IEEE Communications Surveys & Tutorials, early access, 2025.

Takeaway

RIS can become a 6G infrastructure layer that makes wireless environments programmable. The key challenge is moving from ideal single-link simulations to robust, hardware-aware, network-level deployments.

References for this section3

• Q. Wu and R. Zhang, "Towards Smart and Reconfigurable Environment", IEEE Communications Magazine, 2020.
• M. Di Renzo et al., "Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces", IEEE JSAC, 2020.
• A. Tishchenko et al., "The Emergence of Multi-Functional and Hybrid Reconfigurable Intelligent Surfaces for Integrated Sensing and Communications: A Survey", IEEE Communications Surveys & Tutorials, early access, 2025.