Dr Indrasen Singh
Associate Professor in School of Electronics Engineering · Vellore Institute of Technology (VIT) University, Vellore, Tamil Nadu, India
Research Interests
Cooperative communication, stochastic geometry, modeling of wireless networks, heterogeneous networks, millimeter wave communications, Device-to-Device communication, and 5G/6G communication
Biography
Dr. Indrasen Singh is Assistant Professor (Sr. Grade-2) in School of Electronics Engineering (SENSE) at Vellore Institute of Technology (VIT) University, Vellore, Tamil Nadu, India. He received his B. Tech. and M. Tech. Degree in Electronics and Communication Engineering from Uttar Pradesh Technical University, Lucknow, India in 2006, and 2010, respectively. He obtained his PhD degree in Electronics and Communication Engineering from National Institute of Technology Kurukshetra, Haryana, India in 2019. He has more than 12 years of teaching/research experience. He is the editorial board member of AJECE, Science Publishing Group, USA. He has published many research papers in National/International journals/conferences of repute. His research interests are in the area of cooperative communication, stochastic geometry, modeling of wireless networks, heterogeneous networks, millimeter wave communications, Device-to-Device communication, and 5G/6G communication
Education
Ph.D. in Mobile Communication (Department of Electronics & Communication Engineering), 2019, National Institute of Technology, Kurukshetra, Haryana, India M.Tech. (Electronics & Communication Engineering), 2010, Madan Mohan Malviya Engineering College, Gorakhpur, U.P., India (UPTU, Lucknow) with 63.15% B.Tech. (Electronics & Communication Engineering), 2006, NIEC Lucknow (UPTU, Lucknow) with 67.78% Intermediate, 2001, M.G. Inter College Gorakhpur, U.P. Board with 68.60% Matriculation, 1999, M.G. Inter College Gorakhpur, U.P. Board with 67.50%
Recent Scopus Publications
- Quantum-inspired sidelobe canceller beamformer with bidirectional beam scanning and sectorized jamming mitigation properties
- Radio Frequency and Microwave Design for Next Generation Wireless Applications
- An IoT–Machine Learning Proof-of-Concept Framework for Real-Time Urban Particulate Matter Prediction Using Low-Cost Sensors
- Deep Learning-Based Residual and Recovery Framework for Channel Estimation in 5G/B5G Networks
- Analysis and Optimization of Reconfigurable Intelligent Surfaces for 6G Coverage Enhancement
Links
- ORCID https://orcid.org/0000-0001-8274-8079
- Google Scholar https://scholar.google.com/citations?user=Q7QCgsoAAAAJ
- Scopus https://www.scopus.com/authid/detail.uri?authorId=55700309700