Date of Award

3-24-2026

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Engineering Technology

First Advisor

Hussain Al-Rizzo

Abstract

Millimeter-wave (mmWave) Vehicle-to-Infrastructure (V2I) communication is a key enabling technology for next-generation intelligent transportation systems, offering high data rates and low latency to support safety-critical and autonomous driving applications. However, mmWave communication at 28 GHz suffers from severe path loss, sensitivity to blockage, and strong dependence on antenna directivity and beam alignment, particularly in complex urban environments. As a result, advanced beamforming and multi-antenna techniques are essential to ensure reliable and high-capacity V2I links. This thesis investigates mmWave V2I communication performance using realistic electromagnetic modeling and beamforming techniques. Full-wave antenna simulations and deterministic ray-tracing are employed using Ansys Electronics Desktop, including FEM, Hybrid FEM-IE, and SBR+ solvers, to accurately capture antenna behavior, vehicle-body interaction, and propagation effects. An 8×8 microstrip patch antenna array is considered at the base station, while each vehicle is equipped with a 4×4 rooftop-mounted microstrip patch antenna array operating at 28 GHz. Channel State Information (CSI) is extracted from Ansys and processed in MATLAB to implement beamforming algorithms and performance evaluation. Single-user beamforming performance is first analyzed using Maximum Ratio Transmission (MRT) and Zero Forcing (ZF) precoding under free space and urban propagation scenarios, including Line-of-Sight dominant (LoS dominant), Non-Line-of-Sight with LoS dominant (NLoS-LoS dominant), and Non-Line-of-Sight dominant (NLoS dominant) environments. Results demonstrate that beamforming improves received power by 100 %, Signal-to-Interference-plus-Noise Ratio (SINR) by 45 dB, spectral efficiency by 3 bit/s/Hz for SNR below -35 dB and by 14 dB for SNR above 0 dB, and capacity by 1200 Mbps for SNR below -35 dB and by 5600 Mbps for SNR above 0 dB, with performance strongly dependent on propagation conditions and beam alignment accuracy. The thesis further extends the analysis to multi-user beamforming, where multiple vehicles are served simultaneously using Regularized Zero Forcing (RZF) precoding combined with power allocation based on weighted sum-rate maximization. A weighted water-filling solution is applied to balance throughput and fairness among users experiencing different channel conditions, demonstrating the capability of RZF with power allocation to maintain high SINR, enhance spectral efficiency, and capacity even in interference-limited multi-user scenarios. Overall, this thesis highlights the importance of realistic EM modeling, rooftop antenna placement, and advanced beamforming and power allocation strategies for practical mmWave V2I deployments. The presented framework provides valuable insights for the design, analysis, and optimization of reliable, high-capacity mmWave V2I communication systems in both free space and urban scenarios.

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