智能超表面技术白皮书_信道建模与仿真_58页_6mb

Reconfigurable Intelligent Surface (RIS) Technology White Paper Summary

Core Content

Reconfigurable Intelligent Surface (RIS) technology is presented as a promising enabler for 6G mobile networks, with a focus on channel modeling and simulation. The white paper outlines the deployment scenarios, types of RIS, and the methodologies for modeling and simulating RIS-assisted communication channels, aiming to set a baseline for performance evaluation in 3GPP.

Main Views

• RIS Overview: RIS is a quasi-passive technology that can adjust the phase or amplitude of wireless signals to control their propagation direction. It is not a traditional active node or sensing object.
• Deployment Scenarios: RIS is identified as a potential solution for enhancing coverage and throughput in various environments, including outdoor and indoor coverage, O2I/I2O coverage, and low attitude coverage. These scenarios are categorized based on their static or dynamic nature and the frequency range (FR2).
• Evaluation Parameters: Parameters such as transmitters and receivers' properties, RIS properties, and signal attributes are outlined, with some parameters being mandatory and others optional for different scenarios.
• RIS Types: RIS can be classified into types such as reflected, transmitted, STAR, and absorber. The paper emphasizes the use of passive RIS as the first priority, with the potential for active and sensing RIS in future developments.
• Channel Modeling: The channel modeling framework for RIS-assisted communication differs from traditional models, requiring the consideration of three components: BS-RIS, RIS-UE, and the RIS physical model. The model must support accurate simulation across a wide range of frequencies and application scenarios.
• Physical Models: Several physical models for RIS are proposed, including the equivalent radiation pattern model, electromagnetic RCS model, and a simplified cosine radiation pattern model. Each model has its own advantages and trade-offs in terms of complexity and accuracy.
• Simulation Methodology: The paper discusses the use of directional tree graphs for cascaded RIS channel modeling and proposes a framework based on the 3GPP TR 38.901 model for RIS channel modeling.

Key Information

1. Deployment Scenarios

2. RIS Types & Assumptions

• RIS Types: Reflected, Transmitted, STAR, and Absorber.
• RIS Mode: Passive is the first priority, followed by Active, Hybrid, and Sensing.
• RIS Utility: Relay is the first priority, followed by New type Antenna.
• Panel Shape: Plane is the first priority.
• Modulation: Non-information-modulation is the first priority, followed by Information-modulation.
• Modulation Granularity: Continuous is the first priority.
• Polarization: Single and Dual are both considered.
• Assumptions:
  • Lorenz reciprocity based on linear assumption.
  • Frequency range: 0.5 GHz to 100 GHz, same as 3GPP.
  • Bandwidth: No more than 10% of the carrier frequency.
  • Far field assumption between RIS element and receiver.
  • Maximum bouncing number in cascaded RIS scenarios: 2.
  • No reflection from the same RIS element.

3. Channel Modelling Methodology

• General Framework: RIS-assisted communication requires modeling three interconnected components: BS-RIS, RIS-UE, and the RIS physical model.
• Model Requirements:
  • Independent modeling of BS-RIS and RIS-UE links.
  • Accurate phase shift modeling considering scattering patterns, ideal phase shifts, and angle dependencies.
  • Incorporation of non-ideal quantization effects.
• Proposal 4: Based on 3GPP TR 38.901, the framework includes:
  • Constructing per-hop basic channel models (BS-UE, BS-RIS, RIS-UE).
  • Using a virtual RIS base station approach with predefined phase-shift codebooks.
  • Enhancing 3GPP TR 38.901 with height-dependent path loss and absolute time of arrival models.
  • Including both direct and cascaded paths in the final channel model.
• Proposal 5: Directional tree graphs are used to construct cascaded RIS channel models with multiple logical pathways.
• Proposal 6: The equivalent radiation pattern is used to characterize RIS modulation effects. The overall radiation pattern is derived from the superposition of individual element patterns.

4. RIS Physical Model

• Equivalent Radiation Pattern Model:
  • Electric and magnetic fields on the reflection and transmission sides are derived using physical optics.
  • The equivalent radiation pattern is calculated using the formula:
    $$
    f _ {n} ^ {\parallel \perp} \left(\theta^ {i n}, \phi^ {i n}, \theta^ {o u t}, \phi^ {o u t}, R, T\right) = \lim _ {r \rightarrow \infty} \frac {4 \pi}{\lambda} r e ^ {j 2 \pi \lambda^ {- 1} r} \frac {E _ {s} ^ {\parallel}}{E _ {i}}
    $$
  • The overall radiation pattern is the superposition of all RIS elements' effects.
• Electromagnetic RCS Model:
  • Based on physical optics and PEC assumptions, the bistatic RCS for each polarization component is derived.
  • The formula for RCS is:
    $$
    \sigma_ {\text {p o l l}} = \frac {\left| \left(\boldsymbol {n} \times \boldsymbol {H} _ {\mathrm {i} 0 _ \text {p o l l}}\right) \times \boldsymbol {k} _ {\mathrm {s} 0} \right| ^ {2}}{\pi} \cdot \left(k \cdot l _ {x} \cdot l _ {y}\right) ^ {2} \cdot \left{\frac {\sin \left[ \frac {l _ {x}}{2} \left(k _ {s x} - k _ {i x}\right) \right]}{\frac {l _ {x}}{2} \left(k _ {s x} - k _ {i x}\right)} \cdot \frac {\sin \left[ \frac {l _ {y}}{2} \left(k _ {s y} - k _ {i y}\right) \right]}{\frac {l _ {y}}{2} \left(k _ {s y} - k _ {i y}\right)} \right} ^ {2}
    $$
  • The amplitude of the reflection signal is calculated using the formula:
    $$
    \boldsymbol {A} _ {\mathrm {s} _ {-} \text {p o l l}} = \sqrt {\sigma_ {\text {p o l l}} \left(\frac {\left| \boldsymbol {A} _ {\mathrm {i} _ {-} \text {p o l l}} \right| ^ {2}}{\lambda^ {2} / (4 \pi)}\right)} \cdot \frac {\left(\boldsymbol {n} \times \boldsymbol {H} _ {\mathrm {i 0} _ {-} \text {p o l l}}\right) \times \boldsymbol {k} _ {\mathrm {s 0}} \times \boldsymbol {k} _ {\mathrm {s 0}}}{\left| \left(\boldsymbol {n} \times \boldsymbol {H} _ {\mathrm {i 0} _ {-} \text {p o l l}}\right) \times \boldsymbol {k} _ {\mathrm {s 0}} \times \boldsymbol {k} _ {\mathrm {s 0}} \right|} \cdot \sqrt {P L _ {\mathrm {s}}} \cdot \exp (\mathrm {j} \varphi_ {\mathrm {i l}}) \cdot \exp (\mathrm {j} \varphi_ {\text {p o l l}}) \cdot \exp (\mathrm {j} \varphi_ {\mathrm {s l}}) \cdot \sqrt {I _ {\text {l o s s p o l l}}}
    $$

5. System-Level Simulation Assumption for Calibration

• Simulation Assumption:
  • Network layout model.
  • Propagation model.
  • Antenna and beam forming pattern modeling.
  • Other simulation parameters.
• Simulation Methodology: A framework based on 3GPP TR 38.901 is proposed for accurate and efficient simulation of RIS-assisted channels.

6. Conclusions

The white paper provides a comprehensive framework for RIS channel modeling and simulation, aiming to support the standardization and commercial implementation of RIS in 6G networks. It emphasizes the importance of accurate modeling, the use of directional tree graphs, and the integration of physical models such as the equivalent radiation pattern and electromagnetic RCS model. The paper also highlights the need for further research on model complexity reduction and the inclusion of optional features in RIS deployment scenarios.