ECE Oral Comprehensive Exam for Doctoral Candidacy By: Chinmay Mahabal
When: Monday,
January 25, 2021
10:30 AM
-
12:30 PM
Where: > See description for location
Cost: Free
Description: Topic: 5g Based V2v Communication for Autonomous Vehicles
Zoom Teleconference: https://umassd.zoom.com.cn/j/96327292542
Abstract:
The autonomous vehicles are equipped with high definition cameras, Lidars and ultrasonic sensors which require a throughput more than 7 Gbps. The existing 4G LTE is challenged to satisfy these requirements hence the current research is focused on 5G using millimeter waves. The URLLC scheme under 5G is specifically designed for such high reliable low latency communications. This standard assumes channel qualities with a latency less than 0.1 millisecond and a reliability greater than 99.99%. One of the key challenges is the lack of any strong standard due to variability in channel state estimation parameters such high frequencies under 5G.
My study includes analyzing the characteristics of mmWaves by observing changes in pathloss and SNR with distance between the transreceiver. The dynamic nature of the environment causes high interference and drops the Signal to Noise ratio below the acceptable thresholds. A detailed analysis of the 5G architecture is necessary to increase the flexibility in the end-to-end simulation. An overview of inter-related parameters stretched across all the layers of this architecture is studied and the PHY-MAC level communication is simulated using Matlab. By performing extensive literature survey and simulations a platform for Vehicular communication designed for platooning or convoying is proposed as a test bench. This study includes an end-to-end analysis of the existing challenges, their probable solutions and a comparison between them.
The future research directions would include Deep Learning to predict the nonstationary environment parameters and neighboring vehicles for more efficient collective communication, hardware verification of the results on SDRs and special case study for vehicle platooning applications.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Co-Advisors: Dr. Honggang Wang and Dr. Hua Fang
Committee Member: Dr. Ruolin Zhou, Department of Electrical & Computer Engineering, University of Massachusetts Dartmouth; Dr. Qing Yang, Department of Computer Science and Engineering, University of North Texas
*For further information, please contact Dr. Honggang Wang via email at hwang1@umassd.edu.
Zoom Teleconference: https://umassd.zoom.com.cn/j/96327292542
Abstract:
The autonomous vehicles are equipped with high definition cameras, Lidars and ultrasonic sensors which require a throughput more than 7 Gbps. The existing 4G LTE is challenged to satisfy these requirements hence the current research is focused on 5G using millimeter waves. The URLLC scheme under 5G is specifically designed for such high reliable low latency communications. This standard assumes channel qualities with a latency less than 0.1 millisecond and a reliability greater than 99.99%. One of the key challenges is the lack of any strong standard due to variability in channel state estimation parameters such high frequencies under 5G.
My study includes analyzing the characteristics of mmWaves by observing changes in pathloss and SNR with distance between the transreceiver. The dynamic nature of the environment causes high interference and drops the Signal to Noise ratio below the acceptable thresholds. A detailed analysis of the 5G architecture is necessary to increase the flexibility in the end-to-end simulation. An overview of inter-related parameters stretched across all the layers of this architecture is studied and the PHY-MAC level communication is simulated using Matlab. By performing extensive literature survey and simulations a platform for Vehicular communication designed for platooning or convoying is proposed as a test bench. This study includes an end-to-end analysis of the existing challenges, their probable solutions and a comparison between them.
The future research directions would include Deep Learning to predict the nonstationary environment parameters and neighboring vehicles for more efficient collective communication, hardware verification of the results on SDRs and special case study for vehicle platooning applications.
NOTE: All ECE Graduate Students are ENCOURAGED to attend.
All interested parties are invited to attend. Open to the public.
Co-Advisors: Dr. Honggang Wang and Dr. Hua Fang
Committee Member: Dr. Ruolin Zhou, Department of Electrical & Computer Engineering, University of Massachusetts Dartmouth; Dr. Qing Yang, Department of Computer Science and Engineering, University of North Texas
*For further information, please contact Dr. Honggang Wang via email at hwang1@umassd.edu.
Contact:
ECE: Electrical & Computer Engineering Department 508.999.9164 http://www.umassd.edu/engineering/ece/
Topical Areas: General Public, University Community, College of Engineering, Electrical and Computer Engineering