Research Projects

In this proposal, we present a Cooperative Integrated Sensing and Communication framework for Connected Autonomous Vehicle (CAV), referred to as CI-CAV, aimed at enhancing vehicular communication infrastructure. As intelligent mobility advances, the demand for reliable, low latency, and high throughput communication in vehicular environments becomes increasingly critical. However, existing Vehicle to Everything (V2X) technologies such as Dedicated Short Range Communication (DSRC) and Cellular V2X (C-V2X) often fail to meet these requirements, especially in high speed and dynamic scenarios. These systems operate independently of sensing, leading to frequent handoffs, unstable links, and limited adaptability. CI-CAV overcomes these limitations by integrating sensing and communication through cooperative infrastructure. Unlike conventional systems that separate these functions, it enables joint sensing and data exchange across multiple base stations (BSs), providing better situational awareness and proactive link management. This facilitates real time beamforming based on predicted trajectories, reducing latency and improving link reliability. A key feature of CI-CAVs is its adaptive traffic aware strategy, which classifies traffic as Low CAV Flow (LCF) or High CAV Flow (HCF). In LCF, where vehicles are sparse and fast moving, high resolution sensing is activated for trajectory tracking and proactive beam alignment. In HCF, where traffic is dense and slower, sensing is minimized to reduce overhead, while Coordinated Multi Point (CoMP) transmission maintains robust connectivity. Additionally, CI-CAV adopts a dual band communication architecture, combining Sub-6 GHz links for reliable control with Terahertz bands for high data rates and precision sensing. Both layers operate in parallel, using signal combining techniques such as Selection Combining (SC) and Maximum Ratio Combining (MRC) to ensure continuous, high quality connectivity. The framework also proposes a platoon level communication model, where a Master Vehicle (MV) is jointly served by two ISAC enabled BSs through CoMP. These BSs apply radar based sensing and beamforming to establish a strong, low latency link with the MV, which then relays data to Following Vehicles (FVs) via Vehicle to Vehicle (V2V) communication. This master centric edge fusion ensures end to end connectivity for the entire platoon, even amid topology changes or obstructions. To validate CI-CAVs, we will perform MATLAB simulations, system modeling, and algorithm development. Key performance indicators such as SINR, outage probability, beam accuracy, and latency will be assessed under various traffic conditions. The outcome will be a reliable, scalable, and future ready V2X framework aligned with 6G standards, supporting significant advances in vehicular communication.