Hybrid Precoding with Reconfigurable Intelligent Surfaces for Spectral-Efficient Vehicle-to-Infrastructure Communications in Urban 5G NR Networks
Main article
Abstract
The deployment of fifth-generation New Radio (5G NR) millimetre-wave (mmWave) vehicle-to-infrastructure (V2I) communication systems in urban environments confronts severe path loss, intermittent blockage, and rapid Doppler variation that collectively limit coverage, spectral efficiency, and link reliability. This paper proposes a novel hybrid precoding architecture augmented by a Reconfigurable Intelligent Surface (RIS) panel mounted on building facades to establish and maintain high-throughput V2I links even under non-line-of-sight (NLOS) conditions. The proposed framework jointly optimises the digital baseband precoder, the analogue phase-shifting network, and the RIS phase configuration through an Alternating Optimisation (AO) approach combined with Successive Convex Approximation (SCA) to solve the resulting non-convex problem efficiently. A geometry-based stochastic channel model (GSCM) based on the Saleh-Valenzuela formulation, calibrated to the 3GPP TR 38.901 Urban Micro (UMi) propagation scenario at 28 GHz with 200 MHz bandwidth, is employed for all evaluations under vehicle speeds from 30 to 150 km/h. Simulation results demonstrate that the proposed RIS-assisted hybrid precoding scheme achieves a 2.8x improvement in sum spectral efficiency over hybrid beamforming without RIS at 10 dB SNR, and extends effective V2I coverage radius by 112% at 60 km/h. Moreover, energy efficiency analysis confirms a 3.4x gain over full-MIMO at low-to-medium SNR regimes with only 4 RF chains, validating the suitability of the proposed architecture for green, hardware-efficient intelligent transportation systems (ITS). The convergence of the AO-SCA algorithm is verified analytically and empirically, with consistent convergence within 12 iterations.
