Parvathy Nair
Research Staff Member @Bharat Electronics Limited
Signup · Get unlimited contacts
WORK HISTORY
Research Staff Member @Bharat Electronics Limited
Bengaluru, IN
EDUCATION
Indian Institute of Science (IISc)
Master of Technology - MTech, Electronics and Communication Engineering
Veermata Jijabai Technological Institute (VJTI)
Bachelor of Technology - BTech, Electronics Engineering
ABOUT PARVATHY NAIR
I am working as a scientist (member research staff) at the Central Research Laboratory, Bangalore, of Bharat Electronics Limited (BEL) — a Public Sector Undertaking under the Ministry of Defence, Government of India. My work focuses on advancing defence communication technologies, contributing to the development of secure and resilient communication systems for national defence applications.I am passionate about advancing wireless communication technologies, with a focus on 5G Massive MIMO (Multiple Input Multiple Output) systems. My M.Tech research, guided by Dr. Neelesh B. Mehta, centered on enhancing Type-II CSI feedback to improve channel estimation accuracy at the base station. By optimizing feedback in both spatial and frequency domains, I aimed to address critical challenges in reducing feedback overhead for massive MIMO systems.I bring a strong foundation in digital and wireless communication, developed through rigorous coursework and hands-on projects. My experience spans from investigating transmit diversity in narrowband fading channels to implementing trellis-coded modulation with advanced error correction and decoding techniques. These projects have honed my skills in MATLAB, QuaDRiGa, and C programming, enabling me to simulate complex channel conditions, analyze performance metrics, and gain insights into system reliability under diverse scenarios.Driven by a commitment to continuous learning and innovation, I aspire to contribute meaningfully to the fields of digital and wireless communication.Skills: MATLAB, QuaDRiGa, C Programming, Digital Communication, Wireless Communication, Detection and Estimation Theory, Multi-user Detection, Random Processes.
This profile is compiled from publicly available professional sources. Unifers is not affiliated with or endorsed by LinkedIn. Request removal of this profile.