Advanced 5G Wireless Communications: Performance Analysis and Monte-Carlo Simulations

The widespread use of smart devices and their ubiquity has brought up new application domains. One such interesting domain is vehicular networks. The current proposed standards for the Vehicular-to- Vehicular (V2V) communications are Dedicated Short Range Communication (DSRC) and IEEE 1960. US Federal Communication Commission (FCC) has allocated 75Mhz (1 CCH, 6 SCHs (10MHz each)) at 5.9GHz frequencies as Dedicated Short Range Communications (DSRC) Spectrum for vehicular communications. Considering Indian topography and vehicular densities, it becomes challenging to provide sufficient wireless resources to establish the communication between the vehicles using DSRC standard. The solution is to deploy Vehicular Cyber-Physical System (VCPS). However, it requires huge amount of radio spectrum resources hence, spectrum sensing algorithms of Cognitive Radio (CR) Technology is considered a viable solution. CR optimizes the use of available Radio-Frequency spectrum while minimizing the interference to the licensed users. So, with the advent of 5G networks and Intelligent Transport Systems (ITS), it becomes important to address its key requirements.


This Faculty Development Program is especially intended to provide with an in-depth technical exposure of Cognitive Radio, Vehicular Cyber Physical system, Intelligent Transport Systems (ITS) and their utilities in wireless research to the faculty members of engineering colleges, research scholars in wireless communication, post-graduate students, and engineers across the nation. Further interested undergraduate students (UGRP scholars) with good academic record, who would like to further explore the latest research in current wireless systems, can also be a part of this program. The lecture session will include Cognitive Radio (CR), Vehicular Cyber Physical System, Intelligent transport Systems (ITS), and Spectrum Sensing techniques like Energy Detection - Improved Energy Detection in vehicular networks, Imperfect Spectrum Sensing, Spectrum Analytics using Machine Learning followed by three hours of respective lab sessions to further enhance and consolidate the understanding of the participants.


Please click here for the course Brochure.



Highlights of FDP 2017

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