Measurement Based Vehicle-to-Vehicle Multi-link Channel Modeling and Relaying Performance

There has been intense research in vehicular communication in order to provide reliable low-latency vehicular communication links for developing intelligent transportation system (ITS). As one of the important properties, vehicle-to-vehicle (V2V) communication is learned to be inherently non-stationary due to the high mobility of both transmitter (TX) and receiver (RX). Therefore, the V2V system behavior is essentially different from previous mobile communication studies and needs to be understood. For V2V wireless communication systems, it is crucial to model the vehicular channel accurately to evaluate the quality of the system level applications. Among all channel properties in a V2V system, the shadow fading (i.e. large scale fading, LSF) from other vehicles has a significant adverse impact on the system performance. One promising approach to overcome this issue is by implementing multi-hop technology on the vehicular ad hoc network (VANETs). One goal of this thesis report is to implement relaying schemes on simulated Rician channel based on measurements to evaluate the performance of multi-hop technology in V2V systems. Two relaying schemes, Amplify-and-Forward (AF) and Decode-and-Forward (DF), are employed in the bit level simulation. The results of packet error rate (PER) are evaluated together with non-relaying situation for convoy and overtaking scenarios, respectively. Furthermore, a statistic model is created to model the measured highway environment. Pathloss parameters and shadowing loss together with correlation coefficients are derived. Line-of-sight (LOS) and obstructed line-of-sight (OLOS) conditions are manually separated through on-board video. Each scenario has its own parameter set. Maximum likelihood estimation (MLE) is utilized on the pathloss model to compensate the biasing from the measurement hardware. Also the shadowing is modeled as correlated Gaussian and we derived the decorrelation distance from the auto-correlation function (ACF). The model is also validated against the measurements. For an ad hoc network, the diversity schemes would be strongly affected by the multilink correlation. Only a few joint correlation studies for mobile ad hoc network have been made, but rarely for VANETs. The last goal of this report is to study the joint correlation on VANETs based on measurements for four-dimensional position joint correlation model where shadowing is affected by the vehicle distance. To be precise, we focus on the joint correlation of large scale fading affected by the distances between the two receiver vehicles under the same car obstruction. Finally, a stochastic model based on the sum of sinusoids approach is implemented.The fifth generation wireless systems denotes the next major phase of mobile telecommunications standards and is expected to meet consumer demands by 2020. One of the major approach is the vehicular ad hoc networks, which is a spontaneous creation of a wireless network for data exchange to the domain of vehicles. As a key component of the intelligent transportation systems, it is extremely importance to model the vehicular propagation channel in order to meet the requirement of low latency and high reliability. There are many parameters that could describe the channel characteristics. Among them all, the vehicular shadowing has a significant advise impact on the system performance which describes the signal fluctuation affected by an obstruction vehicle. In order to study it, a measurement was designed and took place in Sweden, road Rv 40. Four Volvo cars were forming convoy and overtaking scenarios with equipped signal-transmit-receive devices. Three major works are done in this thesis project based on this measured highway scenario: Firstly, a simulation is designed based on the multi-hop technology. A scenario is simulated where a source car sends packets to a destination car with the help of a relay car. All the packets are randomly generated with each containing proper coding and modulation to enhance the transmission quality as well as to check the success or failure of the transmission. The power properties of the wireless channels between each car-link are captured from the the measurements. They are simulated with a vehicular-based distribution while each byte of the signal would experiences a vehicular channel more close to practice. Two relaying schemes are implemented in the simulation with a different reaction at the relay car after receiving the signal from the source. The destination then combines the two signals from the source and relay. It decodes the signal and records the decoding results. For each observation, the ratio of successfully transmission number and total transmission number is recorded as packet error rate. Eventually, the packet error rate performances of different schemes are compared and evaluated. Secondly, based on whether the link between antennas are obstructed, two scenarios are separated manually by watching the on-board videos. After that, the signal penetration based on transmission distance and the signal fluctuation affected by large obstructions are modeled based on the individual scenario. An advanced estimation method is employed during the modeling of the signal penetration to efficiently include the lost packet information. As for the modeling of the signal fluctuation, an extended distribution is used to describe the facts that, when a transmission link is obstructed by another vehicle, it normally remains obstructed for a certain amount of time. Eventually, channel power can be regenerated based on the model containing the measured channel properties. At last, a model is created to describe the joint effects on the signal fluctuation based on the vehicles' movement and the distances between two receive cars whose signals are obstructed by the same vehicle. The vehicular shadowing following a certain distribution is approximately represented by the sum of many sinusoid waves with random phases and chosen frequencies. The frequencies are generated based on the power and joint correlation properties of the measured channel based on the two effects

Distributed Adaptation Techniques for Connected Vehicles

In this PhD dissertation, we propose distributed adaptation mechanisms for connected vehicles to deal with the connectivity challenges. To understand the system behavior of the solutions for connected vehicles, we first need to characterize the operational environment. Therefore, we devised a large scale fading model for various link types, including point-to-point vehicular communications and multi-hop connected vehicles. We explored two small scale fading models to define the characteristics of multi-hop connected vehicles. Taking our research into multi-hop connected vehicles one step further, we propose selective information relaying to avoid message congestion due to redundant messages received by the relay vehicle. Results show that the proposed mechanism reduces messaging load by up to 75% without sacrificing environmental awareness. Once we define the channel characteristics, we propose a distributed congestion control algorithm to solve the messaging overhead on the channels as the next research interest of this dissertation. We propose a combined transmit power and message rate adaptation for connected vehicles. The proposed algorithm increases the environmental awareness and achieves the application requirements by considering highly dynamic network characteristics. Both power and rate adaptation mechanisms are performed jointly to avoid one result affecting the other negatively. Results prove that the proposed algorithm can increase awareness by 20% while keeping the channel load and interference at almost the same level as well as improve the average message rate by 18%. As the last step of this dissertation, distributed cooperative dynamic spectrum access technique is proposed to solve the channel overhead and the limited resources issues. The adaptive energy detection threshold, which is used to decide whether the channel is busy, is optimized in this work by using a computationally efficient numerical approach. Each vehicle evaluates the available channels by voting on the information received from one-hop neighbors. An interdisciplinary approach referred to as entropy-based weighting is used for defining the neighbor credibility. Once the vehicle accesses the channel, we propose a decision mechanism for channel switching that is inspired by the optimal flower selection process employed by bumblebees foraging. Experimental results show that by using the proposed distributed cooperative spectrum sensing mechanism, spectrum detection error converges to zero

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

Advancement in infotainment system in automotive sector with vehicular cloud network and current state of art

The automotive industry has been incorporating various technological advancement on top-end versions of the vehicle order to improvise the degree of comfortability as well as enhancing the safer driving system. Infotainment system is one such pivotal system which not only makes the vehicle smart but also offers abundance of information as well as entertainment to the driver and passenger. The capability to offer extensive relay of service through infotainment system is highly dependent on vehicular adhoc network as well as back end support of cloud environment. However, it is know that such legacy system of vehicular adhoc network is also characterized by various problems associated with channel capacity, latency, heterogeneous network processing, and many more. Therefore, this paper offers a comprehensive insight to the research work being carried out towards leveraging the infotainment system in order to obtain the true picture of strength, limitation, and open end problems associated with infotainment system

Achieving reliable and enhanced communication in vehicular ad hoc networks (VANETs)

A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirement for the degree of Doctor of PhilosophyWith the envisioned age of Internet of Things (IoTs), different aspects of Intelligent Transportation System (ITS) will be linked so as to advance road transportation safety, ease congestion of road traffic, lessen air pollution, improve passenger transportation comfort and significantly reduce road accidents. In vehicular networks, regular exchange of current position, direction, speed, etc., enable mobile vehicle to foresee an imminent vehicle accident and notify the driver early enough in order to take appropriate action(s) or the vehicle on its own may take adequate preventive measures to avert the looming accident. Actualizing this concept requires use of shared media access protocol that is capable of guaranteeing reliable and timely broadcast of safety messages. This dissertation investigates the use of Network Coding (NC) techniques to enrich the content of each transmission and ensure improved high reliability of the broadcasted safety messages with less number of retransmissions. A Code Aided Retransmission-based Error Recovery (CARER) protocol is proposed. In order to avoid broadcast storm problem, a rebroadcasting vehicle selection metric η, is developed, which is used to select a vehicle that will rebroadcast the received encoded message. Although the proposed CARER protocol demonstrates an impressive performance, the level of incurred overhead is fairly high due to the use of complex rebroadcasting vehicle selection metric. To resolve this issue, a Random Network Coding (RNC) and vehicle clustering based vehicular communication scheme with low algorithmic complexity, named Reliable and Enhanced Cooperative Cross-layer MAC (RECMAC) scheme, is proposed. The use of this clustering technique enables RECMAC to subdivide the vehicular network into small manageable, coordinated clusters which further improve transmission reliability and minimise negative impact of network overhead. Similarly, a Cluster Head (CH) selection metric ℱ(\u1d457) is designed, which is used to determine and select the most suitably qualified candidate to become the CH of a particular cluster. Finally, in order to investigate the impact of available radio spectral resource, an in-depth study of the required amount of spectrum sufficient to support high transmission reliability and minimum latency requirements of critical road safety messages in vehicular networks was carried out. The performance of the proposed schemes was clearly shown with detailed theoretical analysis and was further validated with simulation experiments

Video Streaming over Vehicular Ad Hoc Networks: A Comparative Study and Future Perspectives

Vehicular  Ad Hoc Network  (VANET) is emerged as an important research area that provides ubiquitous short-range connectivity among moving vehicles.  This network enables efficient traffic safety and infotainment applications. One of the promising applications is video transmission in vehicle-to-vehicle or vehicle-to-infrastructure environments.  But, video streaming over vehicular environment is a daunting task due to high movement of vehicles. This paper presents a survey on state-of-arts of video streaming over VANET. Furthermore, taxonomy of vehicular video transmission is highlighted in this paper with special focus on significant applications and their requirements with challenges, video content sharing, multi-source video streaming and video broadcast services. The comparative study of the paper compares the video streaming schemes based on type of error resilient technique, objective of study, summary of their study, the utilized simulator and the type of video sharing.  Lastly, we discussed the open issues and research directions related to video communication over VANET