STAR-RIS-empowered hybrid NOMA/OMA with adaptive modulation for URLLC in finite-blocklength V2X-communications

Abstract

This paper proposes a novel STAR-RIS-assisted hybrid NOMA/OMA framework with adaptive modulation (AM) for ultra-reliable low-latency vehicle-to-everything (V2X) communications under finite blocklength (FBL) constraints. Unlike existing works that separately address STAR-RIS optimization, hybrid multiple access, or URLLC modeling, this study jointly integrates AM, dynamic NOMA/OMA mode switching, and mobility-aware STAR-RIS beam control into a unified FBL-aware design. A roadside unit (RSU) serves a pair of vehicular users with heterogeneous channel conditions, where a STAR-RIS simultaneously transmits and reflects signals to enhance coverage and reliability in high-mobility environments. The core motivation is to overcome the inaccuracy of infinite blocklength assumptions and the rigidity of fixed-access schemes when meeting stringent URLLC latency–reliability requirements. Closed-form reliability expressions are derived for both NOMA and OMA modes under short-packet transmission, explicitly capturing decoding errors, channel dispersion, and imperfect channel state information (CSI). A joint optimization framework based on fractional programming and K-means user clustering is developed to adapt power allocation, modulation order, and access mode selection.Simulation results demonstrate that the proposed SR-AM-URLLC-V2X framework achieves up to 25% higher sum rate, ultra-high reliability (${ϵ}_k\le {10}^{-5}$) at practical SNR levels, and robust performance under vehicular speeds up to 100 km/h, compared to conventional RIS-assisted and fixed-access V2X schemes. These results highlight its effectiveness for safety-critical URLLC-driven V2X communications.