scholarly journals Joint User Clustering and Power Allocation for Vehicular Communications

2020 ◽  
Author(s):  
Qian Chen ◽  
Gongbin Qian ◽  
Chunlong He ◽  
Rujun Zhao ◽  
Yuping Zheng
Keyword(s):  
Power Allocation ◽  
Cellular Network ◽  
Vehicular Networks ◽  
Mixed Integer ◽  
Design Criteria ◽  
Non Linear Programming ◽  
Vehicle To Vehicle ◽  
User Clustering ◽  
Vehicle To Infrastructure ◽  
Allocation Algorithms

Device-to-device (D2D) communication has emerged as a promising concept for supporting the vehicular networks, which can efficient and reliable enhance cellular network. In this paper, we discuss two different design criteria for vehicular networks. They are maximizing overall vehicle-to-infrastructure (V2I) link throughput while guaranteeing the minimum reliability for each vehicle-to-vehicle (V2V) link, and maximizing the minimum throughput of all V2V links under the constraints of minimum V2I link throughput requirements. Because both of these problems is an mixed integer non-linear programming problem, we solve these problems in two steps, i.e., by first clustering D2D users into clusters and then optimizing their respective power allocations. Specifically, we first propose a spectral clustering (SC) method for D2D users clustering. Then, two power allocation algorithms are developed to maximize the sum V2I link throughput and maximize the minimum V2V link throughput, respectively. The effectiveness of proposed resource allocation algorithms is validated by computer simulation.

scholarly journals Propagation and Wireless Channel Modeling Development on Wide-Sense Vehicle-to-X Communications

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Wenyi Jiang ◽  
Ke Guan ◽  
Zhangdui Zhong ◽  
Bo Ai ◽  
Ruisi He ◽  
...  
Keyword(s):  
Communication Technology ◽  
Vehicular Networks ◽  
Channel Modeling ◽  
Transportation Systems ◽  
Wireless Channel ◽  
Wide Sense ◽  
Comprehensive Understanding ◽  
Vehicle To Vehicle ◽  
Wireless Channel Modeling ◽  
Vehicle To Infrastructure

The need for improving the safety and the efficiency of transportation systems has become of extreme importance. In this regard, the concept of vehicle-to-X (V2X) communication has been introduced with the purpose of providing wireless communication technology in vehicular networks. Not like the traditional views, the wide-sense V2X (WSV2X) communications in this paper are defined by including not only vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications but also train-to-X (T2X) communications constituted of train-to-train (T2T) and train-to-infrastructure (T2I) communications. All the information related to the wide-sense V2X channels, such as the standardization, scenarios, characters, and modeling philosophies, is organized and summarized to form the comprehensive understanding of the development of the WSV2X channels.

Witness of Things

2019 ◽  
Vol 7 (2) ◽  
pp. 72-87 ◽  
Author(s):  
Serkan Ayvaz ◽  
Salih Cemil Cetin
Keyword(s):  
Autonomous Vehicles ◽  
Vehicular Networks ◽  
Autonomous Vehicle ◽  
Content Type ◽  
Record Keeping ◽  
Vehicle To Vehicle ◽  
Autonomous Cars ◽  
Vehicle To Infrastructure ◽  
Governmental Institutions ◽  
Self Driving Cars

Purpose The purpose of this paper is to develop a model for autonomous cars to establish trusted parties by combining distributed ledgers and self-driving cars in the traffic to provide single version of the truth and thus build public trust. Design/methodology/approach The model, which the authors call Witness of Things, is based on keeping decision logs of autonomous vehicles in distributed ledgers through the use of vehicular networks and vehicle-to-vehicle/vehicle-to-infrastructure (or vice versa) communications. The model provides a single version of the truth and thus helps enable the autonomous vehicle industry, related organizations and governmental institutions to discover the true causes of road accidents and their consequences in investigations. Findings In this paper, the authors explored one of the potential effects of blockchain protocol on autonomous vehicles. The framework provides a solution for operating autonomous cars in an untrusted environment without needing a central authority. The model can also be generalized and applied to other intelligent unmanned systems. Originality/value This study proposes a blockchain protocol-based record-keeping model for autonomous cars to establish trusted parties in the traffic and protect single version of the truth.

scholarly journals Leveraging Aviation Risk Models to Combat Cybersecurity Threats in Vehicular Networks

Information ◽  
2021 ◽  
Vol 12 (10) ◽  
pp. 390
Author(s):  
Jonathan Ebert ◽  
Ohad Newton ◽  
Jeffery O’Rear ◽  
Scott Riley ◽  
Jaehong Park ◽  
...  
Keyword(s):  
Risk Management ◽  
Vehicular Networks ◽  
Vehicular Network ◽  
Management Process ◽  
Transportation Industry ◽  
Risk Models ◽  
Vehicle To Vehicle ◽  
Risk Management Process ◽  
Vehicle To Infrastructure ◽  
Aviation Risk

The rapidly developing technology and lack of standards in the transportation industry for the proposed Vehicle-to-Vehicle (V2V), Vehicle-to-Infrastructure (V2I), and Vehicle-to-Everything (V2X) networks, which all vehicles will operate under, drives concern about information validity and authenticity due to the risk of erroneous or malicious information being injected into a vehicular network (VN). In this paper, we apply a risk management process to a vehicular network that will identify hazards and possible controls that can lower their risk. After researching and reviewing various technologies along with several risk models, we have developed a basic framework for assessing and assigning risk through a phased method that leads to input for our developed model.

Real Time Acquisition of Traffic Information through V2V, V2R, and V2I Communications

2012 ◽  
pp. 72-92
Author(s):  
Alessandro Bazzi ◽  
Barbara M. Masini ◽  
Gianni Pasolini
Keyword(s):  
Real Time ◽  
Cellular Network ◽  
Insurance Companies ◽  
Traffic Information ◽  
Communication Interface ◽  
Real Time Traffic ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
The Cost ◽  
Time Acquisition

Many vehicles are currently equipped with On-Board Units (OBUs) that are in charge of collecting and processing data for some specific purposes (such as for travel monitoring, as requested by many insurance companies). These devices are connected to the cellular network by means of their Vehicle-to-Infrastructure (V2I) communication interface, and are thus able to transmit and receive information also related to real time traffic, pollution, local events, etc. Of course, as the number of OBU-equipped vehicles increases, the cost of this service increases as well, both in terms of network load and billing. In this chapter, the authors discuss the possibility of taking advantage of vehicle-to-vehicle (V2V) and Vehicle-to-Roadside (V2R) communications to save V2I resources, thus reducing the cellular network burden and, consequently, the service cost.

scholarly journals Power Optimization for Spectrum Sharing in Vehicular Networks

2021 ◽  
Vol 10 (6) ◽  
pp. 10-13
Author(s):  
Thulasimani L. ◽  
A. Antinita Shilpha Daly
Keyword(s):  
Spectrum Sharing ◽  
Vehicular Networks ◽  
Power Optimization ◽  
Hidden Markov ◽  
Vehicular Communication ◽  
Sum Capacity ◽  
High Data ◽  
Vehicle To Vehicle ◽  
Vehicle To Infrastructure ◽  
Harmful Effects

The main goal of vehicular communication is to provide a more safe and efficient vehicular operation. The challenge in a Vehicle-to-Everything (V2X) network is to provide reliable connectivity for the Vehicle-to-Vehicle (V2V) links and high data rate connectivity for the Vehicle-to-Infrastructure (V2I) links at the same time. This requirement leads to spectrum sharing in vehicular communication. As the vehicular systems increases, the transmit power levels increases in the environment which in turn causes harmful effects on the atmosphere. The objective of this paper is to analyze the graph-based spectrum sharing algorithms that are available for vehicular communication and to develop a power optimization algorithm based on Hidden Markov Model (HMM) and to incorporate it into these algorithms in such a way to achieve better sum capacity for the V2I links along with a guaranteed reliability for the V2V links.

scholarly journals Collaborative Autonomous Driving—A Survey of Solution Approaches and Future Challenges

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3783
Author(s):  
Sumbal Malik ◽  
Manzoor Ahmed Khan ◽  
Hesham El-Sayed
Keyword(s):  
Autonomous Vehicles ◽  
Communication Technologies ◽  
Autonomous Driving ◽  
Use Cases ◽  
Cooperative Driving ◽  
Vehicle To Vehicle ◽  
Future Challenges ◽  
Vehicle To Infrastructure ◽  
High Level ◽  
Intersection Management

Sooner than expected, roads will be populated with a plethora of connected and autonomous vehicles serving diverse mobility needs. Rather than being stand-alone, vehicles will be required to cooperate and coordinate with each other, referred to as cooperative driving executing the mobility tasks properly. Cooperative driving leverages Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication technologies aiming to carry out cooperative functionalities: (i) cooperative sensing and (ii) cooperative maneuvering. To better equip the readers with background knowledge on the topic, we firstly provide the detailed taxonomy section describing the underlying concepts and various aspects of cooperation in cooperative driving. In this survey, we review the current solution approaches in cooperation for autonomous vehicles, based on various cooperative driving applications, i.e., smart car parking, lane change and merge, intersection management, and platooning. The role and functionality of such cooperation become more crucial in platooning use-cases, which is why we also focus on providing more details of platooning use-cases and focus on one of the challenges, electing a leader in high-level platooning. Following, we highlight a crucial range of research gaps and open challenges that need to be addressed before cooperative autonomous vehicles hit the roads. We believe that this survey will assist the researchers in better understanding vehicular cooperation, its various scenarios, solution approaches, and challenges.

scholarly journals User Clustering and Power Allocation for Energy Efficiency Maximization in Downlink Non-Orthogonal Multiple Access Systems

2021 ◽  
Vol 11 (2) ◽  
pp. 716
Author(s):  
Ruibiao Chen ◽  
Fangxing Shu ◽  
Kai Lei ◽  
Jianping Wang ◽  
Liangjie Zhang
Keyword(s):  
Energy Efficiency ◽  
Power Allocation ◽  
Multiple Access ◽  
Spectrum Efficiency ◽  
Lagrangian Multiplier ◽  
Efficiency Gain ◽  
Optimal Power Allocation ◽  
Optimal Power ◽  
User Clustering ◽  
Cluster Dynamic

Non-orthogonal multiple access (NOMA) has been considered a promising technique for the fifth generation (5G) mobile communication networks because of its high spectrum efficiency. In NOMA, by using successive interference cancellation (SIC) techniques at the receivers, multiple users with different channel gain can be multiplexed together in the same subchannel for concurrent transmission in the same spectrum. The simultaneously multiple transmission achieves high system throughput in NOMA. However, it also leads to more energy consumption, limiting its application in many energy-constrained scenarios. As a result, the enhancement of energy efficiency becomes a critical issue in NOMA systems. This paper focuses on efficient user clustering strategy and power allocation design of downlink NOMA systems. The energy efficiency maximization of downlink NOMA systems is formulated as an NP-hard optimization problem under maximum transmission power, minimum data transmission rate requirement, and SIC requirement. For the approximate solution with much lower complexity, we first exploit a quick suboptimal clustering method to assign each user to a subchannel. Given the user clustering result, the optimal power allocation problem is solved in two steps. By employing the Lagrangian multiplier method with Karush–Kuhn–Tucker optimality conditions, the optimal power allocation is calculated for each subchannel. In addition, then, an inter-cluster dynamic programming model is further developed to achieve the overall maximum energy efficiency. The theoretical analysis and simulations show that the proposed schemes achieve a significant energy efficiency gain compared with existing methods.

scholarly journals Traffic Flow Management of Autonomous Vehicles Using Platooning and Collision Avoidance Strategies

Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1221
Author(s):  
Anum Mushtaq ◽  
Irfan ul Haq ◽  
Wajih un Nabi ◽  
Asifullah Khan ◽  
Omair Shafiq
Keyword(s):  
Traffic Flow ◽  
Collision Avoidance ◽  
Autonomous Vehicles ◽  
Flow Management ◽  
V2v Communication ◽  
Cooperative Strategies ◽  
Vehicle To Vehicle ◽  
Traffic Flow Management ◽  
Vehicle To Infrastructure ◽  
Formation And Evolution

Connected Autonomous Vehicles (AVs) promise innovative solutions for traffic flow management, especially for congestion mitigation. Vehicle-to-Vehicle (V2V) communication depends on wireless technology where vehicles can communicate with each other about obstacles and make cooperative strategies to avoid these obstacles. Vehicle-to-Infrastructure (V2I) also helps vehicles to make use of infrastructural components to navigate through different paths. This paper proposes an approach based on swarm intelligence for the formation and evolution of platoons to maintain traffic flow during congestion and collision avoidance practices using V2V and V2I communications. In this paper, we present a two level approach to improve traffic flow of AVs. At the first level, we reduce the congestion by forming platoons and study how platooning helps vehicles deal with congestion or obstacles in uncertain situations. We performed experiments based on different challenging scenarios during the platoon’s formation and evolution. At the second level, we incorporate a collision avoidance mechanism using V2V and V2I infrastructures. We used SUMO, Omnet++ with veins for simulations. The results show significant improvement in performance in maintaining traffic flow.

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