Vehicle-to-Everything (V2X) communications play a crucial role in ensuring safe and efficient modern transportation systems. However, challenges arise in scenarios with buildings, leading to signal obstruction and coverage limitations. To alleviate these challenges, reconfigurable intelligent surface (RIS) is regarded as an effective solution for communication performance by tuning passive signal reflection. RIS has acquired prominence in 6G networks due to its improved spectral efficiency, simple deployment, and cost-effectiveness. Nevertheless, conventional RIS solutions have coverage limitations. Therefore, researchers have started focusing on the promising concept of simultaneously transmitting and reflecting RIS (STAR-RIS), which provides 360\degree coverage while utilizing the advantages of RIS technology. In this paper, a STAR-RIS-assisted V2X communication system is investigated. An optimization problem is formulated to maximize the achievable data rate for vehicle-to-infrastructure (V2I) users while satisfying the latency and reliability requirements of vehicle-to-vehicle (V2V) pairs by jointly optimizing the spectrum allocation, amplitudes, and phase shifts of STAR-RIS elements, digital beamforming vectors for V2I links, and transmit power for V2V pairs. Since it is challenging to solve in polynomial time, we decompose our problem into two sub-problems. For the first sub-problem, we model the control variables as a Markov Decision Process (MDP) and propose a combined double deep Q-network (DDQN) with an attention mechanism so that the model can potentially focus on relevant inputs. For the latter, a standard optimization-based approach is implemented to provide a real-time solution, reducing computational costs. Extensive numerical analysis is developed to demonstrate the superiority of our proposed algorithm compared to benchmark schemes.

翻译：车联网（V2X）通信在保障现代交通系统安全高效运行中扮演着关键角色。然而，建筑物场景会引发信号遮挡和覆盖受限等挑战。为缓解这些问题，可重构智能表面（RIS）通过调控无源信号反射被视为提升通信性能的有效方案。RIS因其能提升频谱效率、部署简便且成本效益高，在6G网络中备受关注。但传统RIS方案存在覆盖范围局限，因此研究者开始聚焦于同步透射与反射的RIS（STAR-RIS）这一前瞻性概念——它在继承RIS技术优势的同时可实现360度全覆盖。本文研究了一种STAR-RIS辅助的V2X通信系统，通过联合优化频谱分配、STAR-RIS单元的幅度与相位偏移、面向车对基础设施（V2I）链路的数字波束赋形向量以及车对车（V2V）链路的发射功率，构建了在满足V2V链路时延与可靠性需求条件下最大化V2I用户可达数据速率的优化问题。由于该问题难以在多项式时间内求解，我们将其分解为两个子问题：对于第一个子问题，将控制变量建模为马尔可夫决策过程（MDP），并提出融合注意力机制的组合型双深度Q网络（DDQN），使模型能够聚焦相关输入；对于第二个子问题，采用基于标准优化的方法提供实时解以降低计算成本。大量数值分析表明，与基准方案相比，所提算法具有显著优越性。