Vehicle-to-everything (V2X) communication plays a crucial role in enabling connected and autonomous driving by supporting the reliable exchange of safety-critical information among vehicles and infrastructure. However, due to the open nature of wireless channels, V2X systems are vulnerable to various physical-layer attacks, among which jamming is one of the most intuitive and severe threats. In this paper, we propose a vehicle speed-aware jammer-resilient reception framework for multiuser multiple-input multiple-output (MIMO) V2X systems. The proposed method exploits the fundamental difference in Doppler characteristics between stationary jammers and moving vehicles. By transforming the received signal into the Doppler domain, the receiver identifies low-Doppler components associated with static interference and suppresses them through Doppler-domain filtering. Notably, the proposed approach does not require prior knowledge of the jammer channel or its spatial direction, making it suitable for practical V2X environments. Simulation results demonstrate that the proposed framework effectively mitigates strong jamming signals and significantly improves the achievable sum-rate compared with conventional receivers.
Hanyoung Park, Yongjae Jang, Ji-Woong Choi· International Conference on...· 0 citations
Edge-assisted autonomous driving enables vehicles to offload computationally intensive perception tasks to vehicular edge computing (VEC) servers, thereby reducing on-board power consumption while maintaining real-time performance. However, in practical driving environments, burst traffic and shared workloads among multiple services can significantly increase queue backlogs, potentially degrading system stability and violating latency constraints. In this paper, we propose a traffic-burst-resilient queue-adaptive load balancing algorithm for edge-assisted autonomous vehicles. The proposed method jointly determines task offloading decisions and vehicle central processing unit (CPU) clock frequency using a Lyapunov optimization framework. To enhance robustness under timevarying traffic conditions, we introduce a dynamic trade-off parameter that adaptively adjusts the emphasis between energy efficiency and queue stability based on the current backlog state. When burst traffic causes rapid queue accumulation, the proposed scheme temporarily reduces the energy penalty weight to prioritize backlog stabilization. Simulation results demonstrate that the proposed dynamic parameter design maintains nearly the same level of power consumption as a fixed-parameter baseline, while reducing the average queue backlog by approximately 32%, thereby improving system stability under burst traffic conditions.
Hanyoung Park, Ho-Jun Lee, Yongjae Jang et al.· International Conference on...· 0 citations
