Search Results (40)

Jamming introduces unintentional disruptions in the system to exploit the legitimate communicating equipment. Clustered jamming considers jammers that are present in multiple groups to disrupt the intended communication. Vehicle-to-everything (V2X) transmissions are critical for smart transportation. This research considers full-duplex environment, featuring unmanned aerial vehicles (UAVs) and cellular-base-station-aided V2X (C-V2X) systems exploiting clustered jamming using 3-dimensional (3-D) beam-forming millimeter-wave antennas. UAVs are modeled as a 3-D Poisson point process (PPP), and macro-based tower-mounted base-stations (MBSs) are modeled as a 2-D PPP. Roads are modeled as a Poisson line process. The vehicular nodes (V-Ns) are modeled on each road as a 1-D PPP. The deviations of the UAV’s millimeter-wave band antenna beam follow a Normal distribution. In this paper, for a full-duplex setting, the probabilities of coverage and equipment-association, along with the efficiency of the spectrum associated with various UAV and tower-based connections, are explored in the presence of clustered jamming. The probability of coverage and association of multiple links is derived with respect to the jamming clusters, V-Ns, MBSs, UAVs, jammers’ power, and antenna beams. The results demonstrated that jamming degrades system’s efficiency. This efficiency is further degraded whenever higher 3-D beam-width deviations of the millimeter waveband antenna and jammers are present. Therefore, robust counter-scenarios should be designed for the cases where jamming signals and varying beams disrupt the network. Full article

Millimeter-wave vehicular communication links are prone to blockage and suffer from severe path loss, and high mobility leads to rapidly time-varying channels. In addition, large-scale reconfigurable intelligent surface (RIS) arrays impose substantial channel-estimation overhead and phase-optimization complexity. To address these issues, a group-based and position-aided phase-optimization method is proposed for RIS-assisted millimeter-wave vehicular communications. First, an RIS-assisted uplink system is modeled with a multi-antenna base station (BS), an RIS configured as a uniform planar array (UPA) and a single-antenna vehicular terminal. Channel expressions are formulated for the direct vehicle–BS link, the vehicle–RIS link and the RIS–BS link. Rician fading, line-of-sight (LoS)-dominated millimeter-wave propagation, mobility-induced Doppler shifts and a standardized path-loss model for urban microcell street-canyon scenarios are incorporated to characterize the RIS-assisted vehicular cascaded channel. Based on this model, an optimization problem for the RIS phase-shift matrix is formulated under discrete phase-shift constraints to maximize the achievable rate per unit bandwidth. To avoid the exponential increase in complexity caused by conventional exhaustive search as the number of RIS reflecting elements increases, a successive refinement algorithm is introduced to derive an equivalent channel-gain expression. The original phase-optimization problem is then transformed into an element-wise iterative update process, thereby reducing the computational complexity of large-scale RIS phase configuration. To further reduce the reliance on full channel state information (CSI), two low-overhead phase-optimization schemes are designed. In the group-based scheme, the RIS reflecting elements are partitioned into several subgroups, with all elements in each subgroup constrained to share the same phase shift. This design reduces both the channel-estimation dimensionality and the number of optimization variables. In the position-aided scheme, the spatial coordinates of the BS, RIS and vehicle are used to derive the link distances and the associated angles of arrival and departure. Based on these geometric parameters, the vehicle–RIS–BS cascaded channel is reconstructed and a corresponding phase-alignment strategy is designed. The simulation results demonstrate that both proposed schemes achieve rates of approximately 6.5 bits ${\mathrm{s}}^{-1}{\mathrm{H}\mathrm{z}}^{-1}$ at a transmit power of 30 dBm and outperform existing phase-optimization techniques. When the successive refinement algorithm is applied, the computation time required for phase optimization with a 256-element RIS remains below 0.01 s. Under high-mobility conditions, both proposed schemes approach the performance upper bound achieved with perfect CSI, demonstrating strong robustness to channel variations. Full article

Modern connected and automated vehicles are equipped with various onboard sensors, which continuously generate high-rate perception data. The reliable and timely sharing of such sensor data among neighboring vehicles requires high-capacity and low-latency vehicle-to-vehicle (V2V) communications. Millimeter-wave (mmWave) technology is a promising solution for supporting such high-rate transmission. However, mmWave V2V communication may be severely affected by non-line-of-sight (NLOS) blockage caused by limited transmission range, roadside obstacles, and moving vehicles. Relay forwarding can improve communication reliability and extend transmission distance, while intelligent reflecting surfaces (IRSs) can construct virtual line-of-sight (LOS) links to mitigate NLOS blockage. In this paper, we propose deploying IRSs on urban roadsides to improve mmWave multi-hop V2V communication for vehicular sensor-data sharing by integrating IRS-assisted link selection into multi-hop relay forwarding. However, IRS deployment introduces new challenges in relay selection and directional transmission coordination under interference. To address these challenges, we propose an IRS allocation and relay selection (IARS) scheme for IRS-assisted multi-hop V2V communication. The proposed scheme is based on a transmission evaluation function that jointly considers inter-vehicle distance, link quality, and concurrent transmissions. Simulation results show that the proposed IARS scheme can effectively improve communication reliability and reduce multi-hop delay, thereby supporting reliable and timely sensor-data sharing in urban vehicular networks. Full article

Integrated sensing and communication (ISAC) has emerged as a transformative technology for intelligent transportation systems. Index modulation (IM), recognized for its high robustness and energy efficiency (EE), has been successfully incorporated into ISAC systems. However, most existing IM-based ISAC schemes overlook the spatial multiplexing potential of millimeter-wave channels and remain confined to single-hop vehicle-to-vehicle (V2V) setups, failing to address the challenges of energy consumption and noise accumulation in real-world multi-hop V2V networks with complex road topologies. To bridge this gap, we propose a spatial scattering modulation-based ISAC (ISAC-SSM) scheme and introduce it to multi-hop V2V networks. The proposed scheme leverages the sensed positioning information to select maximum signal-to-noise ratio relay vehicles and employs a detect-amplify-and-forward (DAF) protocol to mitigate noise propagation, while utilizing sensed angle data for Doppler compensation to enhance communication reliability. At each hop, the transmitter modulates index bits on the angular-domain spatial directions of scattering clusters, achieving higher EE. We initially derive a closed-form bit error rate expression and Chernoff upper bound for the proposed DAF ISAC-SSM under multi-hop V2V networks. Both theoretical analyses and Monte Carlo simulations have been made and demonstrate the superiority of DAF ISAC-SSM over existing alternatives in terms of EE and error performance. Specifically, in a two-hop network with 12 scattering clusters, compared with DAF ISAC-conventional spatial multiplexing, DAF ISAC-maximum beamforming, and DAF ISAC-random beamforming, the proposed DAF ISAC-SSM scheme can achieve a coding gain of 1.5 dB, 2 dB, and 4 dB, respectively. Moreover, it shows robust performance with less than a 1.5 dB error degradation under 0.018 Doppler shifts, thereby verifying its superiority in practical vehicular environments. Full article

The emergence of 6G wireless systems marks a paradigm shift toward intelligent, context-aware networks that can adapt in real-time to their environment. Within this landscape, Sensing-Assisted Communication (SAC) emerges as a key enabler, integrating perception into the communication control loop to enhance reliability, beamforming accuracy, and system responsiveness. Unlike prior surveys that treat SAC as a subfunction of Integrated Sensing and Communication (ISAC), this work offers the first dedicated review of SAC in Millimeter-Wave (mmWave) and Sub-Terahertz (Sub-THz) systems, where directional links and channel variability present core challenges. SAC encompasses a diverse set of methods that enable wireless systems to dynamically adapt to environmental changes and channel conditions in real time. Recent studies demonstrate up to 80% reduction in beam training overhead and significant gains in latency and mobility resilience. Applications include predictive beamforming, blockage mitigation, and low-latency Unmanned Aerial Vehicle (UAV) and vehicular communication. This review unifies the SAC landscape and outlines future directions in standardization, Artificial Intelligence (AI) integration, and cooperative sensing for next-generation wireless networks. Full article

Vehicular communication is crucial for the future of intelligent transportation systems. However, providing continuous high-data-rate connectivity for vehicles in hard-to-reach areas, such as highways, rural regions, and disaster zones, is challenging, as deploying ground base stations (BSs) is either infeasible or too costly. In this paper, multiple unmanned aerial vehicles (UAVs) using millimeter-wave (mmWave) bands are proposed to deliver high-data-rate and secure communication links to vehicles. This is due to UAVs’ ability to fly, hover, and maneuver, and to mmWave properties of high data rate and security, enabled by beamforming capabilities. In this scenario, the vehicle should autonomously select the optimal UAV to maximize its achievable data rate and ensure long coverage periods so as to reduce the frequency of UAV handovers, while considering the UAVs’ battery lives. However, predicting UAVs’ coverage periods and optimizing mmWave beam directions are challenging, since no prior information is available about UAVs’ positions, speeds, or altitudes. To overcome this, out-of-band communication using orthogonal time-frequency space (OTFS) modulation is employed to enable the vehicle to estimate UAVs’ speeds and positions by assessing channel state information (CSI) in the Delay-Doppler (DD) domain. This information is used to predict maximum coverage periods and optimize mmWave beamforming, allowing for the best UAV selection. Compared to other benchmarks, the proposed scheme shows significant performance in various scenarios. Full article

With the rapid development of smart connected vehicles, vehicle network communications demand high-speed data transmission to support advanced automotive services. Millimeter Wave (mmWave) communication offers fast data rates, strong anti-interference capabilities, high precision localization and low-latency, making it suitable for high-speed in-vehicle communications. However, mmWave communication performance in vehicular networks is hindered by high path loss and frequent beam alignment updates, significantly degrading the coverage and connectivity of vehicle nodes (VNs). In addition, atmospheric propagation attenuation further deteriorates signal quality and limits system performance due to raindrop absorption and scattering. Therefore, the pure mmWave networks cannot meet the high requirements of highway vehicular communications. To address these challenges, this paper proposes a hybrid mmWave and microwave network architecture to improve VNs’ coverage and connectivity performances through the strategic deployment of Roadside Units (RSUs). Using Radio Access Technology (RAT), mmWave and microwave RSUs are symmetrically deployed on both sides of the road to communicate with VNs located at the road center. This symmetric RSUs deployment significantly improves the network reliability. Analytical expressions for coverage and connectivity in the proposed hybrid networks are derived and compared with the pure mmWave networks, accounting for rainfall attenuation. The study results show that the proposed hybrid network shows better performance than the pure mmWave network in both coverage and connectivity. Full article

Millimeter wave (mmWave) technology, with its ultra-high bandwidth and low latency, holds significant promise for vehicle-to-everything (V2X) communications. However, it faces challenges such as high propagation losses and limited coverage in dense urban vehicular environments. Intelligent Reflecting Surfaces (IRSs) help address these issues by enhancing mmWave signal paths around obstacles, thereby maintaining reliable communication. This paper introduces a novel Contextual Multi-Armed Bandit (C-MAB) algorithm designed to dynamically adapt beam and IRS selections based on real-time environmental context. Simulation results demonstrate that the proposed C-MAB approach significantly improves link stability, doubling average beam sojourn times compared to traditional SNR-based strategies and standard MAB methods, and achieving gains of up to four times the performance in scenarios with IRS assistance. This approach enables optimized resource allocation and significantly improves coverage, data rate, and resource utilization compared to conventional methods. Full article

This work presents a novel dual-polarized antenna array tailored for Internet of Things (IoT) applications, specifically designed to operate in the millimeter-wave (mm-wave) spectrum within the frequency range of 30–60 GHz. Leveraging printed ridge gap waveguide (PRGW) technology, the antenna ensures robust performance by eliminating parasitic radiation from the feed network, thus significantly enhancing the reliability and efficiency required by IoT communication systems, particularly for smart cities, autonomous vehicles, and high-speed sensor networks. The proposed antenna achieves superior radiation characteristics through a cross-shaped magneto-electric (ME) dipole backed by an artificial magnetic conductor (AMC) cavity and electromagnetic bandgap (EBG) structures. These features suppress surface waves, reduce edge diffraction, and minimize back-lobe emissions, enabling stable, high-quality IoT connectivity. The antenna demonstrates a wide impedance bandwidth of 24% centered at 30 GHz and exceptional isolation exceeding 40 dB, ensuring interference-free dual-polarized operation crucial for densely populated IoT environments. Fabrication and testing validate the design, consistently achieving a gain of approximately 13.88 dBi across the operational bandwidth. The antenna’s performance effectively addresses the critical requirements of emerging IoT systems, including ultra-high data throughput, reduced latency, and robust wireless connectivity, essential for real-time applications such as healthcare monitoring, vehicular communication, and smart infrastructure. Full article

Jamming devices introduce unwanted signals into the network to disrupt primary communications. The effectiveness of these jamming signals mainly depends on the number and distribution of the jammers. The impact of clustered jamming has not been investigated previously for an unmanned aerial vehicle (UAV)-assisted cellular-vehicle-to-everything (C-V2X) communications by considering multiple roads in the given region. Also, exploiting three-dimensional (3D) beam-width variations for a millimeter waveband antenna in the presence of jamming for vehicular node (V-N) links has not been evaluated, which influences the UAV-assisted C-V2X system’s performance. The novelty of this paper resides in analyzing the impact of clustered jamming for UAV-assisted C-V2X networks and quantifying the effects of fluctuating antenna 3D beam width on the V-N performance by exploiting millimeter waves. To this end, we derive the analytical expressions for coverage of a typical V-N linked with a line-of-sight (LOS) UAV, non-LOS UAV, macro base station (MBS), and recipient V-N for UAV-assisted C-V2X networks by exploiting beam-width variations in the presence of jammers. The results show network performance in terms of coverage and spectral efficiencies by setting V-Ns equal to 3 km⁻², MBSs equal to 3 km⁻², and UAVs equal to 6 km⁻². The findings indicate that the performance of millimeter waveband UAV-assisted C-V2X communications is decreased by introducing clustered jamming in the given region. Specifically, the coverage performance of the network decreases by 25.5% at −10 dB SIR threshold in the presence of clustered jammers. The performance further declines by increasing variations in the antenna 3D beam width. Therefore, network designers must focus on considering advanced counter-jamming techniques when jamming signals, along with the beam-width fluctuations, are anticipated in vehicular networks. Full article

This review paper provides a comprehensive examination of millimeter-wave radar technologies in automotive systems, reviewing their advancements through signal processing innovations. The evolution of radar systems, from conventional platforms to mmWave technologies, has significantly enhanced capabilities such as high-resolution imaging, real-time tracking, and multi-object detection. Signal processing advancements, including constant false alarm rate detection, multiple-input–multiple-output systems, and machine learning-based techniques, are explored for their roles in improving radar performance under dynamic and challenging environments. The integration of mmWave radar with complementary sensing technologies such as LiDAR and cameras facilitates robust environmental perception essential for advanced driver-assistance systems and autonomous vehicles. This review also calls attention to key challenges, including environmental interference, material penetration, and sensor fusion, while addressing innovative solutions such as adaptive signal processing and sensor integration. Emerging applications of joint communication–radar systems further presents the potential of mmWave radar in autonomous driving and vehicle-to-everything communications. By synthesizing recent developments and identifying future directions, this review stresses the critical role of mmWave radar in advancing vehicular safety, efficiency, and autonomy. Full article

To meet the growing needs of automobile users, and to provide services on demand with stable and efficient paths across different bands amidst this proliferation of users, an integrated approach to the software-defined vehicular network (SDVN) is proposed in this paper. Due to the significant increase in users, DSRC is already considered insufficient to fulfill modern needs. Hence, to enhance network performance and fulfill the growing needs of users in SDVN environments, we implement cognitive technology by integrating the DSRC, mmWave, and THz bands to find stable paths among different nodes. To manage these different technologies, an SDN controller is employed as the main controller (MC), recording the global state of all nodes within the network. Channel sensing is conducted individually for each technology, and sensing results—representing the number of available bands for secondary communications—are updated periodically in the MC. Consequently, the MC manages connections by switching between DSRC, mmWave, and THz bands, providing stable paths between the source and destination. The switching decision is taken by considering both the distance from the MC and the availability of channels among these three technologies. This cognitive integration of bands in SDVN improves performance in terms of network delay, packet delivery, and overhead ratio. Full article

This paper introduces a novel miniaturized, four-mode, semi-flexible leaky wave Multiple-Input Multiple-Output (MIMO) antenna specifically designed to advance vehicular communication systems. The proposed antenna addresses key challenges in 5G low- and high-frequency bands, including millimeter-wave communication, by integrating innovative features such as a periodic Spoof Surface Plasmon Polariton Transmission Line (SSPP-TL) and logarithmic-spiral-like semi-circular strip patches parasitically fed via orthogonal ports. These design elements facilitate stable impedance matching and wide impedance bandwidths across operating bands, which is essential for vehicular networks. The hybrid combination of leaky wave and SSPP structures, along with a defected wide-slot ground structure and backside meander lines, enhances radiation characteristics by reducing back and bidirectional radiation. Additionally, a naturalization network incorporating chamfered-edge meander lines minimizes mutual coupling and introduces a fourth radiation mode at 80 GHz. Compact in size (14 × 12 × 0.25 mm³), the antenna achieves high-performance metrics, including S11 < −18.34 dB, dual-polarization, peak directive gains of 11.6 dBi (free space) and 14.6 dBi (on vehicles), isolation > 27 dB, Channel Capacity Loss (CCL) < 3, Envelope Correlation Coefficient (ECC) < 0.001, axial ratio < 2.25, and diversity gain (DG) > 9.85 dB. Extensive testing across various vehicular scenarios confirms the antenna’s robustness for Vehicle-to-Vehicle (V2V), Vehicle-to-Pedestrian (V2P), and Vehicle-to-Infrastructure (V2I) communication. Its exceptional performance ensures seamless connectivity with mobile networks and enhances safety through Specific Absorption Rate (SAR) compliance. This compact, high-performance antenna is a transformative solution for connected and autonomous vehicles, addressing critical challenges in modern automotive communication networks and paving the way for reliable and efficient vehicular communication systems. Full article

The rapid evolution of smart cities relies heavily on advancements in wireless communication systems and extensive IoT networks. This paper offers a comprehensive review of the critical role and future potential of integrating unmanned aerial vehicles (UAVs) and reconfigurable intelligent surfaces (RISs) to enhance Internet of Vehicles (IoV) systems within beyond-fifth-generation (B5G) and sixth-generation (6G) networks. We explore the combination of quasi-optical millimeter-wave (mmWave) signals with UAV-enabled, RIS-assisted networks and their applications in urban environments. This review covers essential areas such as channel modeling and position-aware beamforming in dynamic networks, including UAVs and IoVs. Moreover, we investigate UAV navigation and control, emphasizing the development of obstacle-free trajectory designs in dense urban areas while meeting kinodynamic and motion constraints. The emerging potential of RIS-equipped UAVs (RISeUAVs) is highlighted, along with their role in supporting IoVs and in mobile edge computing. Optimization techniques, including convex programming methods and machine learning, are explored to tackle complex challenges, with an emphasis on studying computational complexity and feasibility for real-time operations. Additionally, this review highlights the integrated localization and communication strategies to enhance UAV and autonomous ground vehicle operations. This tutorial-style overview offers insights into the technical challenges and innovative solutions of the next-generation wireless networks in smart cities, with a focus on vehicular communications. Finally, future research directions are outlined. Full article

In the next-generation communication systems, multiple access (MA) will play a crucial role in achieving high throughput to support future-oriented services. Recently, rate-splitting multiple access (RSMA) has received much attention from both academia and industry due to its ability to flexibly mitigate inter-user interference in a broad range of interference regimes. Further, with the growing emphasis on spectrum resource utilization, integrated sensing and communication (ISAC) technology, which improves spectrum efficiency by merging communication and radar signals, is expected to be one of the key candidate technologies for the sixth-generation (6G) wireless networks. In this paper, we first investigate the evolution of existing MA techniques and basic principles of RSMA-assisted ISAC systems. Moreover, to make the future RSMA-assisted ISAC systems, we highlight prime technologies of 6G such as non-terrestrial networks (NTN), reconfigurable intelligent surfaces (RIS), millimeter wave (mmWave) and terahertz (THz) technologies, and vehicular-to-everything (V2X), along with the main technical challenges and potential benefits to pave the way for RSMA-assisted ISAC systems. Full article