RIS-Assisted Hybrid Beamforming and Connected User Vehicle Localization for Millimeter Wave MIMO Systems

Area of Science:

• Wireless communication engineering
• Metamaterials and metasurfaces
• Electromagnetic wave propagation

Background:

• Reconfigurable intelligent surfaces (RIS) dynamically control electromagnetic wave reflection and transmission.
• RIS are crucial for improving wireless communication performance, including signal gain and spectral efficiency.
• Millimeter wave (mmWave) vehicle-to-vehicle (V2V) systems face challenges with line-of-sight path blockages.

Purpose of the Study:

• To propose an RIS-assisted hybrid beamforming scheme for blockage-aware mmWave V2V MIMO systems.
• To enhance communication service coverage in mmWave V2V environments.
• To address performance degradation caused by static or mobile blockers.

Main Methods:

• Development of a conjugate gradient and location-based hybrid beamforming (CG-LHB) algorithm to maximize user sub-rate.
• Implementation of a double-step iterative algorithm using error covariance matrix splitting to mitigate location error effects on passive beamforming.
• Evaluation of algorithms under channel uncertainty conditions (below 10%).

Main Results:

• The proposed CG-LHB algorithm effectively addresses user sub-rate maximization.
• The iterative algorithm minimizes the impact of location errors on passive beamforming.
• Simulations validate the effectiveness of the CG-LHB algorithm for RIS-assisted mmWave V2V MIMO systems.

Conclusions:

• The developed RIS-assisted hybrid beamforming scheme improves communication service coverage in mmWave V2V systems.
• The proposed algorithms demonstrate robustness against channel uncertainty.
• This research contributes to overcoming blockage challenges in high-frequency V2V communications.