scholarly journals Preamble-Based Adaptive Channel Estimation for IEEE 802.11p

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2971 ◽  
Author(s):  
Joo-Young Choi ◽  
Han-Shin Jo ◽  
Cheol Mun ◽  
Jong-Gwan Yook
Keyword(s):  
Channel Estimation ◽  
Traffic Safety ◽  
Autonomous Driving ◽  
Frame Structure ◽  
Ieee 802.11P ◽  
Medium Access ◽  
Adaptation Algorithm ◽  
Low Snr ◽  
Overall Performance ◽  
Range Of Values

Recently, research into autonomous driving and traffic safety has been drawing a great deal of attention. To realize autonomous driving and solve traffic safety problems, wireless access in vehicular environments (WAVE) technology has been developed, and IEEE 802.11p defines the physical (PHY) layer and medium access control (MAC) layer in the WAVE standard. However, the IEEE 802.11p frame structure, which has low pilot density, makes it difficult to predict the properties of wireless channels in a vehicular environment with high vehicle speeds; thus, the performance of the system is degraded in realistic vehicular environments. The motivation for this paper is to improve the channel estimation and tracking performance without changing the IEEE 802.11p frame structure. Therefore, we propose a channel estimation technique that can perform well over the entire SNR range of values by changing the method of channel estimation accordingly. The proposed scheme selectively uses two channel estimation schemes, each with outstanding performance for either high-SNR or low-SNR signals. To implement this, an adaptation algorithm based on a preamble is proposed. The preamble is a signal known to the transmitter–receiver, so that the receiver can obtain channel estimates without demapping errors, evaluating performance of the channel estimation schemes. Simulation results comparing the proposed method to other schemes demonstrate that the proposed scheme can selectively switch between the two schemes to improve overall performance.

scholarly journals Efficient Task Offloading for 802.11p-Based Cloud-Aware Mobile Fog Computing System in Vehicular Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Qiong Wu ◽  
Hongmei Ge ◽  
Qiang Fan ◽  
Wei Yin ◽  
Bo Chang ◽  
...  
Keyword(s):  
Traffic Safety ◽  
Vehicular Networks ◽  
Fog Computing ◽  
Autonomous Driving ◽  
Computing System ◽  
Ieee 802.11P ◽  
Computational Capability ◽  
Markov Decision ◽  
The Impact ◽  
Task Offloading

Various emerging vehicular applications such as autonomous driving and safety early warning are used to improve the traffic safety and ensure passenger comfort. The completion of these applications necessitates significant computational resources to perform enormous latency-sensitive/nonlatency-sensitive and computation-intensive tasks. It is hard for vehicles to satisfy the computation requirements of these applications due to the limit computational capability of the on-board computer. To solve the problem, many works have proposed some efficient task offloading schemes in computing paradigms such as mobile fog computing (MFC) for the vehicular network. In the MFC, vehicles adopt the IEEE 802.11p protocol to transmit tasks. According to the IEEE 802.11p, tasks can be divided into high priority and low priority according to the delay requirements. However, no existing task offloading work takes into account the different priorities of tasks transmitted by different access categories (ACs) of IEEE 802.11p. In this paper, we propose an efficient task offloading strategy to maximize the long-term expected system reward in terms of reducing the executing time of tasks. Specifically, we jointly consider the impact of priorities of tasks transmitted by different ACs, mobility of vehicles, and the arrival/departure of computing tasks, and then transform the offloading problem into a semi-Markov decision process (SMDP) model. Afterwards, we adopt the relative value iterative algorithm to solve the SMDP model to find the optimal task offloading strategy. Finally, we evaluate the performance of the proposed scheme by extensive experiments. Numerical results indicate that the proposed offloading strategy performs well compared to the greedy algorithm.

scholarly journals Simulation Based Performance of Mumbai-Pune Expressway Scenario for Vehicle-to-Vehicle Communication Using IEEE 802.11P

2013 ◽  
Vol 14 (4) ◽  
pp. 300-315 ◽  
Author(s):  
Vaishali D. Khairnar ◽  
Ketan Kotecha
Keyword(s):  
Real Time ◽  
Traffic Safety ◽  
High Reliability ◽  
Ieee 802.11P ◽  
Channel Access ◽  
Data Traffic ◽  
Medium Access ◽  
V2v Communication ◽  
Vehicle To Vehicle ◽  
Simulation Scenario

Abstract Traffic safety applications using vehicle-to-vehicle (V2V) communication is an emerging technology and promising area within the ITS environment. Many of these applications require real-time communication with high reliability; to meet a real-time deadline, timely and predictable access to the channel. The medium access method used in 802.11p, CSMA with collision avoidance, does not guarantee channel access before a finite deadline. The well-known property of CSMA is undesirable for critical communications scenarios. The simulation results reveal that a specific vehicle is forced to drop over 80% of its packets because no channel access was possible before the next message was generated. To overcome this problem, we propose to use STDMA for realtime data traffic between vehicles. The real-time properties of STDMA are investigated by means of the highway road simulation scenario, with promising results.

A collection of easily deployable adversarial traffic sign stickers

2021 ◽  
Vol 69 (6) ◽  
pp. 511-523
Author(s):  
Henrietta Lengyel ◽  
Viktor Remeli ◽  
Zsolt Szalay
Keyword(s):  
Traffic Safety ◽  
Autonomous Driving ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Traffic Sign ◽  
Practical Possibility ◽  
Special Knowledge ◽  
Environment Perception ◽  
Assistance Systems ◽  
Traffic Sign Classification

Abstract The emergence of new autonomous driving systems and functions – in particular, systems that base their decisions on the output of machine learning subsystems responsible for environment perception – brings a significant change in the risks to the safety and security of transportation. These kinds of Advanced Driver Assistance Systems are vulnerable to new types of malicious attacks, and their properties are often not well understood. This paper demonstrates the theoretical and practical possibility of deliberate physical adversarial attacks against deep learning perception systems in general, with a focus on safety-critical driver assistance applications such as traffic sign classification in particular. Our newly developed traffic sign stickers are different from other similar methods insofar that they require no special knowledge or precision in their creation and deployment, thus they present a realistic and severe threat to traffic safety and security. In this paper we preemptively point out the dangers and easily exploitable weaknesses that current and future systems are bound to face.

A Slotted Multichannel MAC Protocol for Fair Resource Allocation in VANET

2018 ◽  
Vol 9 (3) ◽  
pp. 45-59 ◽  
Author(s):  
Pant Varun Prakash ◽  
Saumya Tripathi ◽  
Raghavendra Pal ◽  
Arun Prakash
Keyword(s):  
Mac Protocol ◽  
Cluster Head ◽  
Ieee 802.11P ◽  
Medium Access ◽  
Service Channel ◽  
Packet Delivery ◽  
Vehicle Density ◽  
Hidden Terminal ◽  
Future Data ◽  
Multichannel Mac

This article proposes a slotted multichannel medium access control (SMMAC) protocol for VANETs to reduce CCH congestion, decrease RSU dependency, increase safety and data packet's reliability and improve fairness among vehicles. The main entity is the cluster head that not only notifies all the vehicles under the same cluster about the present state of service channel and future data transmissions but also imposes a condition on the maximum number of vehicles allowed inside a cluster. Controlled vehicle density reduces CCH collisions and as a result, it makes the protocol better in terms of packet delivery. To eliminate the inter-cluster hidden terminal problem, in the proposed algorithm, each cluster uses a service channel different from its neighboring cluster. Analyzing the system for both dense and sparse scenario it can be seen through simulation results that the proposed protocol performs much better in comparison to IEEE 802.11p with respect to Throughput, PDR and Delay.

scholarly journals Rolling in the deep

2019 ◽  
Vol 1 (2-4) ◽  
pp. 53-70
Author(s):  
Hannah Biermann ◽  
Ralf Philipsen ◽  
Teresa Brell ◽  
Martina Ziefle
Keyword(s):  
Traffic Safety ◽  
Risk Perceptions ◽  
Data Exchange ◽  
Public Perception ◽  
Autonomous Driving ◽  
Security And Privacy ◽  
Individual Risk ◽  
User Perceptions ◽  
Empirical Procedure ◽  
Qualitative Focus Groups

AbstractAutonomous driving will provide higher traffic safety, meet climate-related issues due to energy-saving mobility, and offer more comfort for drivers. To ensure reliable and safe autonomous traffic, and to provide efficient and time-critical mobility services, data exchange between road users and systems is essential. In public perception, however, sharing data and information may pose a challenge due to perceived privacy restrictions. In this paper, we address user perceptions and their acceptance towards data and information distribution in autonomous driving. In a multi-step empirical procedure, qualitative (focus groups, guided interviews) and quantitative approaches (questionnaire-study) were combined. The findings reveal that autonomous driving is commonly seen as a highly useful and appreciated technology. Though individual risk perceptions and potential drawbacks are manifold, mainly described in terms of data security and privacy-related issues. The findings contribute to research in human-automation interaction, technical development, and public communication strategies.

An Improved Signal Detection Technique for OFDM System

2013 ◽  
Vol 347-350 ◽  
pp. 3527-3531
Author(s):  
Xiao Hong Wang ◽  
Feng Ming Li
Keyword(s):  
Computational Complexity ◽  
Channel Estimation ◽  
Signal Detection ◽  
Detection Probability ◽  
Roc Curves ◽  
Detection Technique ◽  
Ofdm System ◽  
Low Snr ◽  
Awgn Channel ◽  
Simulation Results

In this paper a signal detection technique based on pilots which are transmitted for channel estimation in OFDM system is proposed in AWGN channel. We analyse the algorithm based on pilots and derive an improved signal detection technique. The performance is compared in terms of detection probability and ROC curves are given. The simulation results show that the improved detection technique whose computational complexity is not high can increase the precision of the detection probability at low SNR.

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