Analytical Models of the Performance of C-V2X Mode 4 Vehicular Communications

The C-V2X or LTE-V standard has been designed to support V2X (Vehicle to Everything) communications. The standard is an evolution of LTE, and it has been published by the 3GPP in Release 14. This new standard introduces the C-V2X or LTE-V Mode 4 that is specifically designed for V2V communications using the PC5 sidelink interface without any cellular infrastructure support. In Mode 4, vehicles autonomously select and manage their radio resources. Mode 4 is highly relevant since V2V safety applications cannot depend on the availability of infrastructure-based cellular coverage. This paper presents the first analytical models of the communication performance of C-V2X or LTE-V Mode 4. In particular, the paper presents analytical models for the average PDR (Packet Delivery Ratio) as a function of the distance between transmitter and receiver, and for the four different types of transmission errors that can be encountered in C-V2X Mode 4. The models are validated for a wide range of transmission parameters and traffic densities. To this aim, this study compares the results obtained with the analytical models to those obtained with a C-V2X Mode 4 simulator implemented over Veins

DSRC Versus LTE-V2X: Empirical Performance Analysis of Direct Vehicular Communication Technologies

Vehicle-to-Vehicle (V2V) communication systems have an eminence potential to improve road safety and optimize traffic flow by broadcasting Basic Safety Messages (BSMs). Dedicated Short-Range Communication (DSRC) and LTE Vehicle-to-Everything (V2X) are two candidate technologies to enable V2V communication. DSRC relies on the IEEE 802.11p standard for its PHY and MAC layer while LTE-V2X is based on 3GPP’s Release 14 and operates in a distributed manner in the absence of cellular infrastructure. There has been considerable debate over the relative advantages and disadvantages of DSRC and LTE-V2X, aiming to answer the fundamental question of which technology is most effective in real-world scenarios for various road safety and traffic efficiency applications. In this paper, we present a comprehensive survey of these two technologies (i.e., DSRC and LTE-V2X) and related works. More specifically, we study the PHY and MAC layer of both technologies in the survey study and compare the PHY layer performance using a variety of field tests. First, we provide a summary of each technology and highlight the limitations of each in supporting V2X applications. Then, we examine their performance based on different metrics

Full-duplex UAV relay positioning for vehicular networks

Abstract. The unmanned aerial vehicles (UAVs) can be deployed as aerial base stations or wireless relays to enhance the coverage and guarantee the quality of service (QoS) of wireless networks. In this thesis, the positioning of a full-duplex (FD) UAV as a relay to provide coverage for an FD vehicular network is investigated. This problem is solved using two different methods. In both of the methods, the problem is formulated using a predefined set of locations for the UAV. Then this problem is solved for different configurations of the ground users and an optimal location is selected for the UAV to operate at. In the first approach, given the position of the vehicular users on the ground, a novel algorithm is proposed to find a location for the UAV to satisfy the QoS requirements of the vehicles in the network. The positioning problem is formulated as an $\mathcal{l}_0$ minimization which is non-combinatorial and NP-hard, and finding a globally optimal solution for this problem has exponential complexity. Therefore, the $\mathcal{l}_0$-norm is approximated by the $\mathcal{l}_1$-norm. Simulation results show that by locating the UAV using the proposed algorithm the overall performance of the network increases. In the second approach, the UAV positioning problem is solved using an MAB framework. In this case, a simple scenario where only one source node is communicating with the relay to transmit its message to the base station is considered. Given the location of the source node and the predefined locations of the UAV, the MAB algorithm can successfully identify the optimal location for the UAV so the system achieves the maximum possible sum rate. The Greedy, ϵ-Greedy, and upper confidence bound (UCB) algorithms are used to solve the problem. The comparison of these algorithms based on their regret values reveals that the UCB algorithm outperforms the performance of the other algorithms. Simulation results show that the UCB algorithm can successfully identify the optimal location for the UAV to maximize the sum rate of the communication links

Robust Vehicular Communications Using the Fast-Frequency-Hopping-OFDM Technology and the MIMO Spatial Multiplexing

Vehicle-to-Vehicle communication is one of the more emerging technologies in the 21st century from either the comfortable transportation or safer transportation point of view. Vehicle-to-Vehicle communication has one crucial factor, which is the huge information to be shared among vehicles, such as the position, the road data. In such situation, the accurate information sharing process is the most important factor in order to make the vehicles operating in the most feasible way. This work proposes a more robust vehicle communication system to make the existing vehicle transportation system more efficient. In this paper, we propose a fast frequency hopping orthogonal frequency division multiplexing to mitigate the Doppler spread effect on our previously published clustering benchmark.  This benchmark contains both of a clustering weighting factor based stage and a multiparallel processing stage. This is in addition to modify the PHY layer of the existing IEEE 802.11p standard in order to impose Multiple Input Multiple Output for higher throughput purposes.The results show a noticeable stability compared to our previously published work. Furthermore, the results are almost exceeds the achieved results from the Lower-ID Distributed Clustering Algorithm (DCA) from both of the speed and communication range

SAI: safety application identifier algorithm at MAC layer for vehicular safety message dissemination over LTE VANET networks

Vehicular safety applications have much significance in preventing road accidents and fatalities. Among others, cellular networks have been under investigation for the procurement of these applications subject to stringent requirements for latency, transmission parameters, and successful delivery of messages. Earlier contributions have studied utilization of Long-Term Evolution (LTE) under single cell, Friis radio, or simplified higher layer. In this paper, we study the utilization of LTE under multicell and multipath fading environment and introduce the use of adaptive awareness range. Then, we propose an algorithm that uses the concept of quality of service (QoS) class identifiers (QCIs) along with dynamic adaptive awareness range. Furthermore, we investigate the impact of background traffic on the proposed algorithm. Finally, we utilize medium access control (MAC) layer elements in order to fulfill vehicular application requirements through extensive system-level simulations. The results show that, by using an awareness range of up to 250 m, the LTE system is capable of fulfilling the safety application requirements for up to 10 beacons/s with 150 vehicles in an area of 2 × 2 km2. The urban vehicular radio environment has a significant impact and decreases the probability for end-to-end delay to be ≤100 ms from 93%–97% to 76%–78% compared to the Friis radio environment. The proposed algorithm reduces the amount of vehicular application traffic from 21 Mbps to 13 Mbps, while improving the probability of end-to-end delay being ≤100 ms by 20%. Lastly, use of MAC layer control elements brings the processing of messages towards the edge of network increasing capacity of the system by about 50%

Adaptive cooperative communications for enhancing QoS in vehicular networks

In a vehicular network with high mobility, it is challenging to ensure reliable and efficient connections among vehicles and between vehicles and roadside communication units (or infrastructure) such as base stations or WiFi hot spots. In this paper, we propose a method that utilizes cooperative communications for a combined vehicle-to-infrastructure (V2I) with vehicle-to-vehicle (V2V) approach to improving quality of service (QoS) across the vehicular network. In this approach, we have obtained the closed-form expressions of key QoS performances such as outage probability, throughput, energy efficiency, packet delivery ratio, packet loss rate and average end-to-end-delay for different investigated transmission schemes. These performances can be optimized by adaptively selecting appropriate transmission schemes and, as a results, good trade-offs between system reliability and efficiency can also be achieved under various environmental conditions

The performance of the vehicular communication-clustering process

For the new wireless systems and beyond, the intelligent transportation system is considered as one of the main features that could be covered in the new research topics. Furthermore, both high-speed data transmission and data processing play a crucial role for these generations. Our work covers two main propositions in order to attain an improvement in such intelligent systems performance. A clustering algorithm is proposed and presented for grouping mobile nodes based on their speeds with some modified head assignments processes. This will be combined with a parallel-processing technique that enhances the QoS. Mainly, this work concerns enhancing the V2V data transmission and the processing speed. Thus, a wavelet processing stage has been imposed to optimize the transmitted power phenomenon. In order to check the validity of such proposition, five main efficiency factors have been investigated; namely complementary cumulative distributions, bit rates, energy efficiency, the lifetime of cluster head and the ordinary nodes reattaching-head average times.