# Context-Aware Beam Selection for IRS-Assisted mmWave V2I Communications
## 2 Related Works
### Our Contributions  
These research findings collectively underscore the evolving landscape of IRS-assisted mmWave V2X communication, emphasizing innovation in beam management and selection as a key enabler for its widespread adoption and the improvement in next-generation vehicular communication systems. In addition, these traditional beam selection strategies in vehicular mmWave networks often rely on instantaneous signal strength or static location mapping, which do not reflect future link duration or vehicle mobility patterns. As a result, they tend to cause frequent handovers and unstable links. In contrast, our proposed context-aware framework predicts longer-lasting beam assignments based on high-level contextual factors, reducing switching events and improving average link duration. In this paper, we propose Context-aware Multi-Arm Bandit (C-MAB)-based beam selection for IRS-assisted vehicular communication by incorporating vehicle mobility context under a realistic vehicular mobility environment. The aim is to establish long-lasting connections, unlike signal strength-based approaches for end-to-end V2I communication. Note that, unlike standard C-MAB models, our approach considers a spatiotemporal environment where vehicle mobility and shared beam resources create interaction between decisions. While most C-MABs assume static user contexts and independent arm outcomes, our setting involves overlapping beam coverage, prioritized scheduling, and varying mobility patterns. Therefore, we define reward as the total connection time achieved under a beam, conditioned on the vehicle's context and future trajectory. This formulation aligns more closely with real-world beam stability concerns and differentiates our work from typical bandit designs that focus only on immediate signal gain or throughput. The following describes the main contributions of this paper. * _Context-driven beam and IRS selection_: We introduce a novel approach that leverages a range of contextual factors to enhance the beam and IRS selection process. By considering variables such as vehicle mobility information (e.g., travel directions and relative locations) and traffic light information, we improve the beam and IRS selection process to enable longer-lasting connections. This context-aware selection approach not only improves the overall connectivity quality but also extends the connection time, a critical factor in V2X communication, especially for mission-critical applications. * _Predictive testing tool for IRS locations_: Recognizing the importance of IRS placement in achieving optimal signal reflections, we offer a practical tool for assessing the effectiveness of IRS locations. This tool empowers network planners and engineers to simulate IRS deployments and assess their impact on signal propagation before actual implementation. By doing so, we mitigate the risk of suboptimal IRS placement, thereby enhancing the overall performance and robustness of mmWave V2X communication systems. * _Utilization of traffic light waiting times_: This is the first work to incorporate waiting times at traffic lights as contextual data for predicting beam sojourn times in IRS-assisted V2I communication. This predictive insight allows for the development of proactive mobility and resource management strategies. By factoring in traffic light cycles, we can optimize beam switching, resource allocation, and mobility planning, ensuring that the V2I communication system remains seamless and uninterrupted, even in stop-and-go traffic scenarios. Note that the traffic light status can be acquired through standard V2X interfaces supported by modern infrastructure. Traffic controllers broadcast phase and timing information (e.g., current light status, remaining time, next transition) using SPaT messages [19]. These data can be received directly by the base station via wired connectivity or wirelessly via Roadside Units (RSUs) that act as V2I relays.