Jul 2026· International Conference on Ubiquitous and Future Networks· pp. 361-365· 0 citations· 26 references
Abstract
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.
This paper investigates vehicle-to-vehicle (V2V) integrated sensing and communication (ISAC) networks under ultra-reliable low-latency communication (URLLC) constraints in the presence of a vehicular eavesdropper (VE). To address the lack of instantaneous eavesdropper channel state information (CSI) in high-mobility scenarios, a vehicular jammer (VJ) is employed to perform radar-based sensing and extended Kalman filter (EKF)-based tracking of the VE’s kinematic state. The estimated state information and its posterior uncertainty are shared with the legitimate transmitter and are used to construct uncertainty-aware spatial covariance matrices for the VE-related channels. Based on these covariance matrices, the VJ transmits artificial noise (AN) in the null space of the legitimate receiver, thereby degrading the VE’s reception while avoiding interference to the intended link. In this context, a finite-blocklength (FBL) secrecy-rate framework is developed together with a two-time-scale optimization strategy, where the sensing resources are optimized at the slot level to enhance EKF tracking accuracy, while the transmit covariance and AN covariance matrices are optimized at the frame level to maximize the average FBL secrecy rate. The resulting non-convex problem is handled through semidefinite relaxation (SDR), alternating optimization (AO), and successive convex approximation (SCA). Simulation results show that the proposed framework improves secrecy robustness against mobility and sensing-induced spatial uncertainty.
E. T. Michailidis, Theodoros A. Tsiftsis, N. Miridakis· Italian National Conference...· 0 citations
: Connected vehicles rely on Vehicle to Everything (V2X) communication to enable safety critical and cooperative driving applications. The open nature of wireless channels makes these systems vulnerable to physical layer jamming attacks, which can disrupt message exchange and potentially compromise traffic safety. In this paper, we present an integrated co-simulation framework that models jamming attacks in connected vehicular networks using OMNeT++, SUMO, and Veins. We emulate realistic barrage style jamming through protocol compliant interference at the IEEE 802.11p physical layer and evaluate its impact on key communication metrics including Packet Delivery Ratio (PDR), latency, and channel utilization. We further implement Frequency Hopping Spread Spectrum (FHSS) as a mitigation strategy and assess its effectiveness under sustained interference. Our results show that a single 200 mW jammer reduces PDR from 100% to 9.1%, and that FHSS reduces SNIR corrupted frames by 63.3% while simultaneously suppressing jammer throughput by 49%. Beyond the security evaluation, this work contributes a modular, reproducible simulation framework explicitly designed to support the vehicular security research community.
Kumoulica Allu, Yun-Peng Zhang, Chang-Qing Luo et al.· International Conference on...· 0 citations
This paper presents a novel 6G-Enabled vehicle-to-everything (V2X) communication framework designed for the Intelligent Internet of Vehicles (IoV). The proposed system integrates the multi-user access and interference suppression capabilities of multi-carrier code division multiple access (MC-CDMA) with the delay–Doppler domain robustness of orthogonal time frequency space (OTFS) modulation. This hybrid design ensures reliable transmission in high-mobility and dense vehicular environments. Vehicle mobility is modeled using a combination of car-following dynamics and Markov chain-based lane-changing behavior, capturing both longitudinal and lateral motion patterns. The communication system further employs minimum mean square error (MMSE) and zero-forcing (ZF) techniques for multi-user detection at the receiver. To cope with rapid channel variations caused by mobility, we introduce a Multi-Agent Deep Q-learning (DQL) framework for mobility-aware channel tracking. Each agent learns adaptive channel update strategies based on historical channel estimates and mobility context. Simulation results show that the proposed MC-CDMA–OTFS system with DQL tracking achieves up to a 2.5 dB SNR gain at BER = 10⁻³ and improves throughput compared to a conventional OFTS baseline. These findings highlight the potential of the proposed hybrid design as a robust physical-layer foundation for next-generation 6G V2X networks.
T. H. Nguyen, Anh Thuy Nguyen· Vietnam Journal of Science a...· 0 citations
With Vehicle-to-Vehicle (V2V) communication being one of the enabling elements for intelligent transportation systems and autonomous driving, it enables a reliable one-to-one exchange of safety-related information, including vehicle speed, inter-vehicular distance, braking systems, and the surrounding roadway environment. The highly dynamic nature of vehicular environments, combined with stringent reliability, latency, and energy-consumption requirements, makes it natural to adopt communication architectures that are both spectrally and hardware- and power-efficient. In this context, the current paper explores an intelligent surface (RIS) aid V2V communication system that makes use of a suggested dual-polarized spatial modulation (DPSM) scheme employing one active RF chain per symbol interval over four physical antennas. The suggested architecture makes use of spatial, polarization, and RIS-generated degrees of freedom to augment the adaptability of linkages with significantly lower RF hardware complexity and power usage. Detailed system-level simulations are conducted in realistic conditions, utilizing 3GPP V2V/V2X fading channel models that incorporate vehicle mobility and urban propagation conditions. Major performance indicators, such as received signal strength indicator (RSSI), reference signal received power (RSRP), reference signal received quality (RSRQ), bit error rate (BER), and signal-to-noise ratio (SNR), as well as energy efficiency, are strictly measured and compared with conventional full-MIMO performance. Simulation results demonstrate that the RIS-assisted single-active-RF-chain DPSM scheme can achieve significant energy efficiency gains while maintaining competitive BER performance across a wide SNR range. Where, the transmitter uses physical dual-polarized antennas which provide 8 logical spatial-modulation ports, i.e.,4 antennas× 2 polarizations, but only one RF chain and one logical port are active in each symbol interval. These enhancements in RSSI, RSRP and RSRQ highlight the ability of RIS to provide signal shaping and polarization diversity to reduce the harsh fading and blockage characteristics of the V2V operating environment in the urban environment. Although the full-MIMO system exhibits better BER performance due to its increased spatial diversity, the proposed DPSM architecture offers a more advantageous trade-off between performance, complexity, and energy. These results support the use of the RIS-supported DPSM architecture as a highly suitable and convenient design for next-generation V2V communications, particularly on systems with power- and cost-limited vehicle platforms.
Shane E Lewis, M. P. Darshan, Praveen Kumar et al.· PLoS ONE· 0 citations
Addressing the dual threats of malicious jamming and time-varying fading faced by wireless communication links in complex dynamic electromagnetic adversarial environments, existing intelligent anti-jamming methods predominantly focus on single-dimensional resource optimization under quasi-static channels. This focus neglects the nonlinear superposition effects of multi-path deep fading and dynamic strong jamming in the time-frequency domain, making it challenging for systems to balance transmission reliability and system energy efficiency in physical environments where fading and suppression coexist. To address this issue, this study proposes a joint intelligent anti-jamming method for channel switching and transmit power control based on a Deep Q-Network (DQN). Initially, a composite communication environment model incorporating Markov time-varying fading and jamming is constructed. Subsequently, the joint resource scheduling problem is formulated as a Markov Decision Process. The environment state space is reconstructed by integrating continuous channel state estimation and jamming observation features, accompanied by the design of a highly aggregated two-dimensional discrete action space for both channel and power. Finally, a composite reward function evaluating both communication success rates and power consumption costs is proposed to guide the agent in multi-dimensional resource joint optimization. Simulation results demonstrate that the proposed algorithm effectively extracts implicit features under the composite state of fading and jamming. When encountering extreme deep fading or full-band blocking, the agent strategically triggers a silent mechanism to avoid exorbitant invalid energy consumption penalties, while precisely matching interference-free channels with the minimum effective transmit power during favorable communication windows. Simulation results show that compared with traditional xx algorithms, the proposed method significantly improves the dynamic successful transmission rate and system energy efficiency in complex, highly dynamic scenarios, achieving an effective optimization of anti-jamming reliability and low power overhead.
By incorporating integrated sensing and communication (ISAC) into vehicle-to-infrastructure (V2I) networks, roadside units (RSUs) can support data transmission while providing additional sensing capabilities, thereby enabling intelligent transportation services. By deploying large-scale antenna arrays at RSU, the V2I network can realize more reliable connectivity and more accurate vehicle tracking by harnessing the significant beamforming gains provided by the enlarged antenna aperture. However, it is not energy efficient to realize such arrays using conventional phased arrays, which rely on numerous power-hungry phase shifters. To address this, this demo presents the first reconfigurable intelligent surface (RIS)-based ISAC-empowered vehicular network prototype, which operates at sub-6 GHz band to be compatible with existing vehicular systems. The RIS has a low power consumption of 6.8W. Experimental results show that compared with the system without RIS, the proposed RIS-based prototype enables more accurate vehicle trajectory tracking with an average localization error of 0.11m and supports more robust data transmission, as evidenced by a 41.9% reduction in error vector magnitude (EVM). These results validate the effectiveness of the RIS-based ISAC system for supporting vehicular networks.
Sheng Yang, Yuhan Wang, Shuhao Zeng et al.· 0 citations
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