Paper Info
Title
Feasibility of 5G mm-wave communication for connected autonomous vehicles.
Abstract
The internet-of-things (IoT) environment holds different intelligent components networked together and will enable seamless data communication between the connected components. Connected autonomous vehicles or CAVs are major components of the IoT, and the smooth, reliable, and safe operation of CAVs demands a reliable wireless communication system, which can ensure high connectivity, high throughput and low communication latency. The 5G millimeter-wave or mm-wave communication network offers such benefits, which can be the enabler of CAVs, especially for dense congested areas. In this research, we have evaluated the 5G mm-wave and Dedicated Short Range Communication (DSRC) for different CAV applications in a Network Simulator-3 (ns-3). For the CAV applications, we have evaluated the end-to-end latency, packet loss, and data rate (for both the CAV receiver and transmitter) of the 5G mm-wave. We have found that 5G mm-wave can support CAV safety applications by ensuring lower latency compared to the required minimum latency of 200 milliseconds for the forward collision warning application. For mobility applications, we have found that 5G mm-wave can support multiple CAVs with a high data receive rate, which is enough for real-time high definition video streaming for in-vehicle infotainment, with mean packet delay of 13 milliseconds. The findings from this study establish that 5G mm-wave can be the enabler of future CAVs in congested areas. Using the evaluation framework developed in this paper, public agencies can evaluate 5G mm-wave to support CAVs in congested areas, such as heavy pedestrian areas like downtown, commercial zones, under their jurisdiction.
Year
Venue
Field
2018
arXiv: Networking and Internet Architecture
High-definition video,Transmitter,Telecommunications network,Latency (engineering),Computer science,Network packet,Computer network,Packet loss,Throughput,Dedicated short-range communications
DocType
Volume
Citations 
Journal
abs/1808.04517
0
PageRank 
References 
Authors
0.34
11
4
Name
Order
Citations
PageRank
Sakib Mahmud Khan1105.51
Mashrur Chowdhury216324.22
Mizanur Rahman312920.97
Mhafuzul Islam433.12