Natural disasters often damage the ground infrastructure, leading to communication failures that hamper emergency response efforts. Solutions dependent on ground-based infrastructure suffer from severe limitations in these scenarios owing to fixed positions, limited energy sources, and limited coverage. Existing methodologies, often relying on terrestrial relay points or fixed infrastructure, face

With the presence of an array of passive elements embedded in a reconfigurable intelligent surface (RIS), estimation of time-varying channels between a fast-moving user and the fixed base station (BS) is more challenging than conventional static channels. In this paper, we propose a joint technique for the estimation of carrier frequency offset (CFO) and doubly selective channel (DSC), and data detection

In recent years, Vehicular Ad-hoc Networks (VANETs) have gained widespread acceptance to enable vehicles to communicate and exchange critical information, such as road conditions, traffic congestion, speed, and vehicle locations. Nonetheless, the wireless nature of VANET communication renders it susceptible to various security attacks. To counter these vulnerabilities, privacy-preserving authentication

This article investigates the joint optimization of task offloading and computation scheduling in low Earth orbit (LEO) satellite networks, where each LEO satellite is equipped with a reconfigurable intelligent surface (RIS). By considering the inherent characteristics of tasks and the energy consumption associated with task execution, we define a system utility function and formulate the problem as

Vehicular networking plays an indispensable role in enhancing road safety and traffic efficiency. Although existing technologies have made significant progress in reusing vehicle-to-infrastructure (V2I) link resources for vehicle-to-vehicle (V2V) links, they still face challenges such as the high dimensionality of the joint action space and unsatisfactory optimization with limited in-vehicle radio

The suddenness of natural disasters demands rapid response and timely information. The rapid development of unmanned aerial vehicle (UAV) technology offers new opportunities for post-disaster assessment. At the same time, UAV swarms covering multiple post-disaster regions also face challenges. Uneven UAV utilization and region allocation can lead to overuse and excessive energy consumption of certain

To ensure reliable data transmission in flying ad hoc networks (FANETs), efficient routing protocols are necessary to establish communication paths in FANETs. Recently, reinforcement learning (RL), particularly Q-learning, has become a promising approach for overcoming challenges faced by traditional routing protocols due to its capacity for autonomous adaptation and self-learning. This study presents

Recently, the rapid development of wireless technologies, low-priced equipment, advances in networking protocols, and access to modern communication, electrical, and sensing technologies have led to the evolution of flying ad hoc networks (FANETs). However, the high movement of unmanned aerial vehicles (UAVs) in these networks causes iterated failures of communication links and constant changes in

This paper investigates the potential of Free Space Optical (FSO) communication technology for high-speed train (HST) systems by developing mathematical models for G2T-FSO (Ground to Train) communication links across single, curved, and double-curved tracks. The key contribution of this research is the introduction of novel G2T-FSO models, incorporating multiple transmitters (single, double, triple

Positioning is a crucial element of the new connected world and its integration with the current and future releases of the mobile system technology has been gaining interest since the introduction of the 5G verticals. In the application layer, positioning provides an additional and, in many cases, a fundamental value for the implementation of services like terrestrial and non-terrestrial vehicles

This paper considers a mobile jammer-aided unmanned aerial vehicle (UAV) relay communication system, where a relay UAV assists information transmission between the source node and the destination node, while a friendly jammer UAV emits an interference signal to the eavesdropper to suppress its eavesdropping behavior. The secure energy efficiency (SEE) maximization problem is studied. The objective

Non-orthogonal multiple access (NOMA) has recently been integrated into beamspace multiple-input multiple-output (MIMO) for improved capacity and throughput. To apply the promising beamspace MIMO-NOMA in practical millimeter-wave applications, finite blocklength has to be considered. Therefore, in this article, we consider the effective throughput as the performance metric, which incorporates both

Empowered with edge caching technology, the near-end storage resources of edge nodes in the Internet of Vehicles (IoV) can be fully utilized to accelerate the process of responding to content requests. In this paper, we propose a cooperative edge caching scheme utilizing regional feature and dynamic vehicle clustering (CRFDC). We take into consideration the fact that the change frequency of content

The delay-sensitive applications, such as self-driving, smart transportation, navigation, and augmented reality assistance, can be evolved in vehicular ad-hoc networks (VANETs) using one of the leading paradigms, fog computing (FC). The intelligent vehicles are connected to the roadside infrastructure, such as high power nodes (HPNs) and roadside units (RSUs), also called fog nodes (FNs), for obtaining

The self-interference caused by simultaneous uplink and downlink transmissions, along with inter-cell co-channel interference, significantly challenges the benefits of full-duplex transmission in future multi-UAV assisted Air-Ground Integrated OFDMA Networks. Effective resource allocation is crucial for achieving high system performance in these complex full-duplex environments. This paper investigates

Internet of Vehicles (IoV) uses a variety of communication technologies to connect vehicles, road infrastructure, and the cloud to achieve real-time information exchange and intelligent interaction between vehicles, vehicles and infrastructure, vehicles and service providers so as to improve traffic safety, traffic efficiency, and ride experience. Some scholars have proposed the use of Multipath Transmission

The extensive application of the Metaverse in the Internet of Vehicles (IoV) has provided broader application scenarios and innovative opportunities for intelligent vehicle travel. The implementation of the Metaverse, which necessitates low latency, high precision, and swift feedback and interaction, can be effectively addressed by harnessing unmanned aerial vehicle (UAV)-assisted IoV technology. However

Unmanned Aerial Vehicle (UAV)-assisted Internet of Things (IoT) applications vary widely including data monitoring, data collection and analysis, intelligent navigation and object tracking, surveillance and emergency response, vehicular and intelligent transport, and agricultural, marine, and photogrammetry. Mobile Edge Computing (MEC)-based UAV-assisted IoT networks enable resource-constrained mobile

This study explores the need for efficient resource allocation in fifth generation (5G) New Radio (NR) sidelink communication for cellular vehicle-to-everything (C-V2X) applications. With the advent of 5G networks, C-V2X can enable direct connection between neighboring vehicles and infrastructure without relying on the cellular network. However, direct communication between devices in 5G NR sidelink

Unmanned aerial vehicles (UAVs) are being developed as a promising technology to assist mobile edge computing (MEC) systems due to their reliable wireless communication, flexible computing service capabilities, and flexible deployment. However, in the face of huge information and demanding task delay, it is a challenging problem to reduce the system cost. This paper studies task offloading and cache

Mobile Edge Computing (MEC) effectively alleviates the computational burden faced by vehicles in processing compute-intensive tasks due to resource limitations. However, traditional approaches typically employ coarse-grained task offloading strategies that utilize sequential protocols and discrete action spaces, resulting in high latency and increased energy consumption. These limitations render such

In vehicular networks, the increasing demand for computational resources often exceeds the capabilities of in-vehicle devices. To address these challenges, we propose a cloud-edge-device collaborative framework integrated with a Multi-Agent Deep Reinforcement Learning (MADRL) algorithm for dynamic optimization of task offloading and resource allocation. Experimental evaluations demonstrate the proposed

Vehicular Ad Hoc Networks (VANETs) are high-speed mobile wireless communication networks that play a pivotal role in shaping the future of intelligent transportation systems. In many fields, certificateless aggregate signcryption (CLASC) serves as a reliable method that reduces computational and communication overheads while enhancing security. Due to these advantages, in recent years, an increasing

In complex and high-mobility vehicular communication networks, rapidly changing channel conditions, signal interference, and stringent latency requirements of safety services pose significant challenges to existing wireless resource allocation schemes. We propose a novel resource allocation method named AMADRL. It is based on the multi-agent deep reinforcement learning (MADRL) algorithm and incorporates

Advanced air mobility, the next evolution in air transportation, emphasizes the crucial need for a high level of automation to enable the coexistence of manned and unmanned aircraft and transform airspace from segregated to unsegregated, empowering aircraft to manage self-separation and collision avoidance autonomously. This paper introduces a separation assurance and collision avoidance that adopts

Integrated Vehicular Networks (VANETs) constructed through the collaboration of various heterogeneous networks, such as 4G, 5G, satellite networks, and Unmanned Aerial Vehicle (UAV) networks, provide an effective solution to the resource constraints between vehicles and edge fog computing nodes. Reordering Buffer (RB) is crucial in concurrent data transmission between vehicles and edge fog computing

Cooperative, Connected and Automated Mobility (CCAM) is a new paradigm adopted by academia and industry in order to provide safe, secure and sustainable mobility on all kinds of roads (highways, urban and rural roads). CCAM takes advantage of Cooperative Intelligent Transport Systems (C-ITS) to improve safety and to reduce traffic congestion thanks to communication and cooperation among all relevant

As a key contribution, this article presents the first successful application of the newly developed Vivaldi Non-uniform Profile Antenna (VNSPA) theory to a Vivaldi Tapered Slot Antenna (VTSA) operating in the 26 GHz band (24.25–27.5 GHz). The proposed design achieves both compactness and simplicity while maintaining high performance. This antenna is a promising candidate for vehicular communication

The surge in wireless network attacks has intensified the focus on physical layer security (PLS) within academia and industry. As PLS provides security solutions by leveraging the randomness of wireless channels without the need for encryption/decryption keys, fading channels play a major role in PLS solutions. This survey aims to understand the effect of fading on PLS for 5G/6G communications by utilizing

Vehicular digital twin network is partitioned into multiple networks either due to the geographical differences or their accelerating expansion, which necessitates a secure and incessant transition of cross-regional vehicles. Therefore, in this dynamic topology, the handover process for cross-regional vehicles becomes imperative. The literature encompasses an abundance of blockchain-based handover

Currently, resource allocation in Unmanned Aerial Vehicles (UAVs) is a major topic of discussion among industrialists and researchers. Considering the different emerging applications of UAVs, if the resource allocation problem is not addressed effectively, the upcoming UAV applications will not serve their proposed purpose. Although there are numerous and diverse research works addressing the resource

The vehicle ad hoc network, or VANET, is a fantastic tool for smart transport since it improves efficiency, management, traffic safety, and comfort. Distributed Denial of Service (DDoS) attacks on VANET infrastructure have the potential to compromise traffic safety by causing collisions and fatalities. Therefore, while integrating VANETs into intelligent transport networks, the pertinent security issues

Detecting zero-day attacks is a critical challenge in the Internet of Vehicles (IoV). Due to the limited availability of labeled attack data, anomaly-based methods are predominantly employed. However, the variability in the driving environment and behavioral patterns of vehicles introduces significant fluctuations in normal behavior, which in turn leads to high false positive rates when using these

The next generation (5G/B5G) vehicular cognitive radio networks (VCRNs) flag the track to intelligence-based autonomous driving in the initiation of future wireless networking and make daily vehicular operation more convenient, greener, efficient, and safer. However, with the continuous evolution of vehicles, the vehicular network becomes large-scale, dynamic, and heterogeneous, making it tough to

Flying ad hoc networks (FANETs) are a new example of ad hoc networks, which arrange unmanned aerial vehicles (UAVs) in an ad hoc form. The features of these networks, such as the movement of UAVs in a 3D space, high speed of UAVs, dynamic topology, limited resources, and low density, have created vital challenges for communication reliability, especially when designing routing methods in FANETs. In

Connected Vehicles (CVs) are a crucial element in the evolution of smart transportation systems, utilizing communication and sensing technologies to interact with each other and with infrastructure. As these vehicles become more interconnected, the risk of their components being affected by anomalies or intentional malicious attacks grows. It is essential, therefore, to identify and filter out any

Data aggregation is evolving into an extremely crucial role for facilitating decision-making in Internet of Vehicles (IoV). Multi-region data is a typical attribute of IoV, containing sensitive information and driving trajectories. However, the existing privacy-preserving schemes face problems such as regional statistics, messages integrity, and collusion attacks. In order to tackle this challenge

In low-altitude economic logistics scenarios, trajectory planning for unmanned aerial vehicles (UAVs) can be treated as a typical traveling salesman problem (TSP). High-rise buildings in urban areas not only severely impact the flight safety of UAVs, but also increase their energy consumption when avoiding obstacles, thereby affecting their delivery ranges. To address these issues, this paper proposes

Digital twin (DT) provides a powerful framework to enable various intelligence applications in vehicular edge computing networks. DT servers are used to model and optimize the resource allocation of the whole dynamic system, to provide low latency services for the vehicles. However, the dynamic topology and varying network status make it a challenge to construct the DT model timely, especially in the

This paper addresses the challenges of selecting relay nodes and coordinating among them in UAV-assisted Internet-of-Vehicles (IoV). Recently, UAVs have gained popularity as relay nodes to complement vehicles in IoV networks due to their ability to extend coverage through unbounded movement and superior communication capabilities. The selection of UAV relay nodes in IoV employs mechanisms executed

Vehicular edge computing (VEC) is beneficial to reduce task offloading delay and service acquisition delay by pushing cloud functions to the edge of the networks. Edge servers have the computation and storage capacity to execute vehicular tasks and cache the services required for tasks execution. Due to the limited caching resources of a single edge server, the vehicles will obtain services from cloud

Connected and Autonomous Vehicles (CAVs) are pivotal to the evolution of Intelligent Transportation Systems (ITS), offering enhanced connectivity and automation. However, the emergence of quantum computing poses significant security challenges to existing cryptographic protocols. This study addresses these challenges by proposing a hybrid security approach that combines Kyber Post-Quantum Cryptography

Unmanned aerial vehicles (UAVs) are an emerging technology with the potential to be used in industries and various sectors of human life to provide a wide range of applications and services, significantly enhancing its applicability in different fields. When a UAV swarm performs complex tasks, flying Ad-hoc networks (FANETs) based on cluster structures have become a key research topic in the field

Autonomous vehicles for intelligent surveillance in rural areas increasingly demand low-cost and reliable data collection technologies to perform dense monitoring across extended areas. Backscattering communication has been employed for this purpose, primarily for low-cost and energy efficiency reasons. This paper considers a backscattering data collection system empowered by unmanned aerial vehicles

Vehicle-to-Everything (V2X) communications are constrained by both 3GPP technical specifications, as well as by country-specific spectrum regulations. The world's largest economies, such as the USA, EU and China have self-imposed regulations regarding the specific bandwidths and central spectrum frequencies where both safety and non-safety related V2X communication services are allowed to occur (always

Due to the shortage of energy resources and computational capability, unmanned aerial vehicles (UAVs) tend to fail to execute tasks with time-delay sensitive and complex demands like artificial intelligence (AI) enabled applications. Most offloading method literature in ground-air cooperative systems simply uses edge servers or remote cloud servers to provide computation resources and storage space

Reconfigurable Intelligent Surfaces (RISs) provide a promising avenue for enhancing performance and implementation efficiency in multiuser wireless communication systems by enabling the manipulation of radio wave propagation. In this paper, an Augmented Jellyfish Search Optimization Algorithm (AJFSOA) is specifically designed to optimize the achievable rate in RIS-equipped systems. AJFSOA distinguishes

The humble, mechanical automobile has gradually evolved into our modern connected and autonomous vehicles (CAVs)—also known as “smart vehicles.” Similarly, our cities are gradually developing into “smart cities,” where municipal services from transportation networks to utilities to recycling to law enforcement are integrated. The idea, with both smart vehicles and smart cities, is that more data leads

With the proliferation of Internet of Things, leveraging federated learning (FL) for collaborative model training has become paramount. It has turned into a powerful tool to analyze on-device data and produce real-time applications while safeguarding user privacy. However, in vehicular networks, the dynamic nature of vehicles, coupled with resource constraints, gives rise to new challenges for efficient

This paper presents VeTraSPM (Vehicle Trajectory Data Sequential Pattern Mining), a novel algorithm designed to address the limitations of existing sequential pattern mining methods when applied to vehicle trajectory data. Current algorithms fail to capture essential characteristics such as directional flow on one-way roads (e.g., “AB” is valid but not “BA”), connectivity constraints at junctions,

The vehicle platoon using the cooperative adaptive cruise control (CACC) transmits information between vehicles via communication networks to increase the control performance. However, time delays are inevitable during the network transmission of information, which influence the stability of the CACC vehicle system. This paper proposes a method for compensating information affected by time delays based

The integration of several developing technologies and their applications with Internet of Vehicles (IoVs) techniques has been improved. Utilizing these emerging technologies renders the in-vehicle network more susceptible to intrusions. Furthermore, the utilization of Electronic Control Units (ECUs) in current vehicles has experienced a significant increase, establishing the Controller Area Network

Traffic offloading is crucial for reducing computing latency in distributed edge systems such as vehicle-to-everything (V2X) networks, which use roadside units (RSUs) and access network mobile edge computing (AN-MEC) with ML agents. Traffic offloading is part of the control plane problem, which requires fast decision-making in complex V2X systems. This study presents a novel ratio-based offloading

In this study, we present an in-depth analysis of communication services for commercial airline passengers, focusing on the challenges posed by increasing internet traffic demand. We explore the integration of satellite, airborne, and terrestrial networks, emphasizing the roles of Low Earth Orbit (LEO) satellites, High-Altitude Platform Station (HAPS), and Terrestrial Aviation Network (TAN)-based services

With the rise and development of intelligent vehicles, the computation capability of vehicles has increased rapidly and considerably. Vehicle-to-Vehicle (V2V) offloading, in which computation-intensive tasks are offloaded to underutilized vehicles, has been proposed. However, V2V offloading faces the challenges of task transmission reliability and task computation reliability. In V2V offloading, tasks

With the vigorous development of Internet of Vehicles (IoV) technology, modern cars equipped with advanced on-board systems are continuously generating massive amounts of data. Utilizing this data can improve driving safety and achieve better service quality in smart transportation systems. Therefore, ensuring the efficiency and security of data sharing is an important issue. Integrating IoV and blockchain

Edge caching is an effective paradigm that can significantly reduce the computation task offloading latency for mobile edge computing (MEC) in vehicular networks, while also alleviating the backhaul transmission pressure for retrieving content data from the cloud server. However, most existing works fail to address how to handle heterogeneous tasks generated by vehicle terminals (VTs), especially in

The rapid advancements in wireless communication have underscored the need for innovative solutions to enhance network performance, spectral efficiency, and energy savings. Intelligent Reflecting Surface (IRS) technology has emerged as a transformative approach that passively reconfigures wireless propagation environments, offering significant improvements without active power consumption. This survey

Vehicular Ad Hoc Network (VANET) has risen as a paramount technology for efficiently providing traffic management, safety and infotainment services to road users. Vehicles are allowed to use pseudo identities during vehicular network access to preserve their privacy. This property makes VANET vulnerable to Sybil attack, performed by exploiting the set of pseudo identities to send messages. Detecting