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We are on the cusp of a new era of connected autonomous vehicles with unprecedented user experiences, tremendously improved road safety and air quality, highly diverse transportation environments and use cases, and a plethora of advanced applications. Realizing this grand vision requires a significantly enhanced vehicle-to-everything (V2X) communic...
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... are another potential aerial communication platform for 6G-V2X communications. An example of a satellite-assisted V2X communication system is illustrated in Fig. 6. In current V2X standards, satellites are currently only used for localization purposes. It is worth mentioning that the data rates of satellite communication have been increasing significantly in recent years. For example, multibeam satellites [97] have been widely adopted in satellite communication systems due to their capability to ...
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... Improved air interfaces, resource allocation [29], decision making, and computation are just some of the cutting-edge technologies that 6G will need to implement to reach its lofty promises. Support from UAVs and low earth orbit satellites [30] may help V2X systems improve communication quality in areas where traditional terrestrial communication systems may have blind spots. ...
... 6G V2X system[29] ...
... In recent years, OTFS has been proposed as a new 2D modulation scheme in [2]. OTFS introduces the delay-Doppler (DD) domain to represent the wireless channel [3], which can effectively convert the double-dispersion channel into a DD-domain approximation non-fading channel, so that all symbols in each frame obtain almost the same channel gain, which enables OTFS to simultaneously have ultra-high-speed, low-latency, and high-reliability information interaction capability and high-precision, high-accuracy, and high-resolution full-time all-day sensing capability in high-mobility communication scenarios [4]. This feature has led researchers to extensively introduce OTFS into V2X communications. ...
Aiming at the problem that existing channel estimation methods are unable to track the channel parameter variations within a single frame under continuous Doppler spread channel (CoDSC) which leads to serious estimation errors, this paper proposes a basis expansion model (BEM) orthogonal time frequency space (OTFS) channel estimation method based on Cluster-Pruning Stagewise Weak Orthogonal Matching Pursuit (CP-SWOMP). This method first uses a discrete prolate spheroidal sequences (DPSS) as a basis function to model the channel response, converting the underdetermined channel estimation into a sparse reconstruction problem with basis coefficients. Then the basis coefficients are solved for using compressed sensing methods, the nearest neighbor clustering criterion is introduced into the Stagewise Weak Orthogonal Matching Pursuit (SWOMP) algorithm, and the atoms of the iterative intermediate process are subjected to a quadratic pruning operation, which solves the redundancy problem of the support set and improves the reconstruction accuracy. In this paper, multiple methods are simulated and validated at different normalized Doppler frequency, and the results demonstrate that the proposed method can achieve better normalized mean square error (NMSE) and bit error rate (BER) performance with less pilot overhead.
... In fact, 3GPP has evolved 5G NR through different Releases, making it more suited to support ITS. Unfortunately, 5G NR-based V2X networks will not be able to fulfill the strict requirements of future V2X services [3], empowering the design of 6G. ...
Vehicle-to-Everything (V2X) networks will constitute a prominent application in future generations of cellular networks, definitely transforming our conception of transportation systems. A major challenge in V2X networks is the vast amount of data generated by the large number of sensors in the vehicles, which saturates the wireless links. As it is not possible to meet the throughput, timing, and reliability requirements for the total bulk of generated data, one needs to filter out data based on the actual communication goal. In this paper we present an architecture and diverse options to implement filtering and source coding for goal-oriented vehicular communications. We illustrate how filtering and source coding contribute to meeting the strict delay requirements while maintaining energy-efficient operation. Our results show that goal-oriented communications, performed as the combination of Bloom filtering and goal-oriented source coding, can greatly contribute not only to reduce the energy consumption by up to 30% but also to decrease delay, which in turn increases the supported amount of delay-sensitive traffic by up to 819.2%.
... This includes supporting advanced applications for CAVs, such as cooperative perception using raw sensor data, mobile edge intelligence and remote driving. Furthermore, 6 G systems operating on the THz band have significant potential in the areas of positioning, sensing and 3D imaging, in addition to the communication advantages they provide (He et al., 2021;Noor-A-Rahim et al., 2022). ...
Intelligent Transportation Systems (ITS) are gaining momentum due to the advantages it possesses in congestion-free traffic, reduced probability of accidents, and economical transit thus reducing the transit time, saving human life, and helping the growth of the economy. Autonomous vehicles (AV) are an important part of ITS as these are the actual actuators of the ITS. In AVs, the perception system is particularly important as this provides vital information to the motion and planning system. Any error in perception of the environment by the AV will lead to the failure of the entire ITS. This article provides a thorough review of the recent technological advancements in perception systems. In this work, we have considered peer-reviewed journals and conference proceedings on AV from 2019 onwards. The primary focus is on motion prediction models, object detection, localization, sensor data fusion, sensors, autonomous driving (AD), communication technology and AI. This article also discusses the various challenges faced by perception systems in AD and how communication technology and Artificial Intelligence (AI) can help the perception system to overcome the existing challenges.
... With the development of intelligent transportation, vehicleto-everything (V2X) communication has become extremely essential [1]. However, as the number of vehicles has grown explosively, V2X needs to address several critical challenges, such as massive access, spectrum and energy shortages. ...
... In this work, we consider an AmBC-NOMA-assisted highmobility V2X scenario as depicted in Fig. 1, which consists of a roadside unit (RSU), a BD, a near vehicular user (denoted by U N ), and a far vehicular user (denoted by U F ). 1 All the nodes are equipped with single antenna. ...
In this paper, we investigate the performance of ambient backscatter communication non-orthogonal multiple access (AmBC-NOMA)-assisted short packet communication for high-mobility vehicle-to-everything transmissions. In the proposed system, a roadside unit (RSU) transmits a superimposed signal to a typical NOMA user pair. Simultaneously, the backscatter device (BD) transmits its own signal towards the user pair by reflecting and modulating the RSU's superimposed signals. Due to vehicles' mobility, we consider realistic assumptions of time-selective fading and channel estimation errors. Theoretical expressions for the average block error rates (BLERs) of both users are derived. Furthermore, analysis and insights on transmit signal-to-noise ratio, vehicles' mobility, imperfect channel estimation, the reflection efficiency at the BD, and blocklength are provided. Numerical results validate the theoretical findings and reveal that the AmBC-NOMA system outperforms its orthogonal multiple access counterpart in terms of BLER performance.
... There are two communication modes: one for direct vehicular communications via the UU air interface under the coverage of the cellular network, and another for the out-of-coverage area of the cellular network via the PC5 interface [126]. Currently under development, 6G-V2X communication technology is the latest technology in the THz band and can support even better hyper-fast, ultra-reliable, and low-latency communication compared to 5G-NR [136]. Cellular V2X (C-V2X) consists of 4G-LTE or 5G-NR communication technologies and thus can cost-efficiently provide a longer range than Wi-Fi with the extended detection of the coverage and blind spots [26]. ...
... ensuring critical and safe vehicle sensors connectivity; used for keeping safe distance and speed between vehicles, connection with roadside infrastructure, sensing of other roadside participants; can overcome LOS issues with long-range perception using cellular networks [26] LoRa (Based on IEEE 802. 15.4) Up to 20 km According to research, LoRa can cope with real-world scenarios with actual vehicles at higher speeds and a dynamic environment in terms of reliability and performance [27] 6G-V2X (under development) -Massive information exchange technology by combining several communication networks, e.g., satellite and unmanned-aerial-vehicle (UAV) networks, with a combination of ML methods [136] 4G LTE V2X (3GPP Rel. 14,15) Up to 20 km Can be used as an alternative to Wi-Fi; 4G LTE does not support C-V2X applications as well 5G NR, although the infrastructure is more deployed [2,132] NB IoT (3GPP Rel. ...
Autonomous systems are becoming increasingly relevant in our everyday life. The transportation field is no exception and the smart cities concept raises new tasks and challenges for the development of autonomous systems development which has been progressively researched in literature. One of the main challenges is communication between different traffic objects. For instance, a mobile robot system can work as a standalone autonomous system reacting to a static environment and avoiding obstacles to reach a target. Nevertheless, more intensive communication and decision making is needed when additional dynamic objects and other autonomous systems are present in the same working environment. Traffic is a complicated environment consisting of vehicles, pedestrians, and various infrastructure elements. To apply autonomous systems in this kind of environment it is important to integrate object localization and to guarantee functional and trustworthy communication between each element. To achieve this, various sensors, communication standards, and equipment are integrated via the application of sensor fusion and AI machine learning methods. In this work review of vehicular communication systems is presented. The main focus is the researched sensors, communication standards, devices, machine learning methods, and vehicular-related data to find existing gaps for future vehicular communication system development. In the end, discussion and conclusions are presented.
... This includes vehicle-to-vehicle (V2V), vehicle-to-device (V2D), vehicle-to-pedestrian (V2P), and even vehicle-to-infrastructure (V2I) [64]. Up to this point, two primary technologies have been developed to enable V2X communications, which are based on either dedicated shortrange communications (DSRCs) or cellular network connections [65]. DSRCs operate in a part of the Unlicensed National Information Infrastructure (U-NII) frequency bands, more specifically in the 5.9 GHz U-NII-4 band (5.850-5.925 ...
The proliferation of the Internet of Things (IoT) propels the continuous demand for compact, low-cost, and high-performance multiband filters. This paper introduces a novel low-profile dual-band bandpass filter (BPF) constructed with a back-to-back coupled pair of shielded folded quarter-mode substrate integrated waveguide (SF-QMSIW) multimode cavities. A hybrid structure is obtained by etching a coplanar waveguide (CPW) coupling line in the folded cavity’s septum layer. It serves multiple functions: generating an additional resonance, providing a separate coupling mechanism for the upper passband, and offering the flexibility to control the passbands’ center frequency ratio. Additionally, the unused second higher-order mode is suppressed by integrating embedded split-ring resonators (ESRRs) with an inter-digital capacitor (IDC) structure into the feed lines. A filter prototype has been fabricated and experimentally tested. The measurements confirmed reliable operation in two passbands having center frequencies 3.6 GHz and 5.8 GHz, and exhibiting 3 dB fractional bandwidths (FBWs) of 6.4% and 5.3%, respectively. Furthermore, the group delay variation within both passbands equals only 0.62 ns and 1.00 ns, respectively. Owing to the second higher-order mode suppression, the filter demonstrated an inter-band rejection exceeding 38 dB, within a compact footprint of 0.71λg2 (with λg being the guided wavelength at the lower passband’s center frequency).
... Unlike traditional frequency bands, mmWave signals are highly susceptible to attenuation from environmental factors such as foliage, atmospheric conditions, and even building materials. Consequently, the effectiveness of UAVs in establishing robust connections with CEVs and the BS is diminished, compromising the reliability and throughput of IoV [15][16][17]. Moreover, the dynamic nature of UAV deployment exacerbates the challenges associated with maintaining stable connectivity in 5G and B5G environments. ...
This paper integrates intelligent reflecting surfaces (IRS) with unmanned aerial vehicles (UAV) to enhance the transmission performance of the Internet of Vehicles (IoV) through non-orthogonal multiple access (NOMA). It focuses on strengthening the signals from cell edge vehicles (CEVs) to the base station by optimizing the wireless propagation environment via an IRS-equipped UAV. The primary goal is to maximize the sum data rate of CEVs while satisfying the constraint of the successive interference cancellation (SIC) decoding threshold. The challenge lies in the non-convex nature of jointly considering the power control, subcarrier allocation, and phase shift design, making the problem difficult to optimally solve. To address this, the problem is decomposed into two independent subproblems, which are then solved iteratively. Specifically, the optimal phase shift design is achieved using the deep deterministic policy gradient (DDPG) algorithm. Furthermore, the graph theory is applied to determine the subcarrier allocation policy and derive a closed-form solution for optimal power control. Finally, the simulation results show that the proposed joint phase shift and resource management scheme significantly enhances the sum data rate compared to the state-of-the-art schemes, thereby demonstrating the benefits of integrating the IRS-equipped UAV into NOMA-enhanced IoV.
... It allows vehicles to communicate with other vehicles, infrastructure, pedestrians, networks, and devices in real time [88]. The main goal of V2X communications is to improve the safety, efficiency, and convenience of transportation by providing information and services that can assist drivers, passengers, and road users [89], [90]. There are several types of V2X communications, depending on the target entity: ...
... In traffic management, URLLC's reliable and instantaneous communication is vital for the rapid transmission of traffic data and emergency alerts, contributing to smoother traffic flow and enhanced road safety. V2X is integral to both traffic management and environmental monitoring [89], [126]. It enables vehicles to communicate with traffic infrastructure, other vehicles, and even pedestrian devices. ...
With 5G technology evolving, Open Radio Access Network (O-RAN) solutions are becoming crucial, especially for handling the diverse Quality of Service (QoS) needs in vehicular networks. These networks are dynamic and have many different applications, calling for effective O-RAN strategies. This paper examines a three-tier hierarchical O-RAN slicing model, created to address the unique challenges of vehicular networks. The top-level follow 3GPP standards like ultra-reliable and low-latency communications (URLLC), enhanced mobile broadband (eMBB), and massive machine-type communications (mMTC). The middle level is organized by vehicle types, and the lowest level is designed for specific vehicle applications. This approach leads to better network resource management. Additionally, this study explores the advantages of a federated deep reinforcement learning (DRL) approach for efficient learning while maintaining privacy. It introduces a federated DRL approach incorporating federated averaging and deep deterministic policy gradient (DDPG) techniques, to enhance inter-slice operations and resource allocation in vehicular networks. Lastly, the effectiveness of this algorithm is demonstrated through a small simulation in a vehicular framework.
... The QoS guaranteed spectrum resource allocation was proposed in [19] which performed spectrum resource allocation to maximize system throughput while satisfying different QoS requirements of vehicle to infrastructure (V2I) links. By combining NOMA and vehicle to everything (V2X) can mitigate resource conflicts, improve spectral efficiency and reduce latency [20]. Two relay-assisted NOMA transmission architectures for V2X communication were Content courtesy of Springer Nature, terms of use apply. ...
In this paper, a non-orthogonal multiple access vehicle-to-vehicle (NOMA-V2V) cooperative system model is proposed. The outdated channel state information (CSI) is derived based on the three-dimensional two-cylinder channel model. The residual interference is derived using outdated CSI to characterize the degree of successive interference cancellation (SIC), i.e., perfect SIC and imperfect SIC. A power allocation scheme is proposed to maximum the sum achievable rate of NOMA-V2V cooperative system under consideration of residual interference. The corresponding power allocation scheme of OMA-V2V cooperative system is proposed. And achievable rates and outage probabilities of the NOMA-V2V and OMA-V2V cooperative systems are derived. The effects of power allocation coefficient, imperfect SIC, transmission power and the distance between transmitting and receiving ends on the achievable rates and outage probabilities are analyzed for the NOMA-V2V cooperative system. These results are compared with the OMA-V2V cooperative system. It provides theoretical guidance for V2V cooperative network to choose which multiple access method.
