CV


Mojtaba Hajiabadi

Mojtaba Hajiabadi

Assistant Professor

Faculty: Electrical and Computer Engineering

Department: Electronic

Degree: Ph.D

CV
Mojtaba Hajiabadi

Assistant Professor Mojtaba Hajiabadi

Faculty: Electrical and Computer Engineering - Department: Electronic Degree: Ph.D |

Dr. Mojtaba Hajiabadi, a graduate of Electrical Engineering with a focus on Telecommunication Systems, earned his Bachelor's degree in 2012 from the University of Birjand, his Master's degree in 2014, and his Ph.D. in 2018 from Ferdowsi University of Mashhad. He was an outstanding student, holding third rank in his Bachelor's, first in his Master's, and first in his Ph.D. In 2018, he completed a doctoral research opportunity at KU Leuven University in Belgium under the supervision of Professor Marc Moonen, a distinguished IEEE Fellow.

During his Ph.D., Dr. Hajiabadi received several awards from the National Elites Foundation, including research grants, teaching assistantships, and an international research opportunity grant. After completing his studies, he worked for five years in Iran's telecommunications industry, contributing to satellite communication transceivers in the aerospace sector and optical telecommunication systems at the Infrastructure Communications Company. Since 2022, he has been a full-time faculty member in the Communication Engineering Department, Faculty of Electrical and Computer Engineering, at the University of Birjand. His research interests include adaptive filters, machine learning, and AI in wireless communication systems.

If you are interested in collaborating on research in his field of expertise, you may contact him via the following email address:

Email: mhajiabadi@birjand.ac.ir

نمایش بیشتر

Adaptive Channel Estimation for MIMO-OFDM Systems in Impulsive Noise Environments

AuthorsMojtaba Hajiabadi
Conference Titleسیزهمین کنفرانس بین المللی مهندسی کامپیوتر و دانش
Holding Date of Conference2023-11-01
Event Placeمشهد
Page number0-0
PresentationSPEECH
Conference LevelInternal Conferences

Abstract

Multiple-input multiple-output (MIMO) systems with orthogonal frequency-division multiplexing (OFDM) techniques provide a credible high-speed wireless communication system. To realize the efficiency of a MIMO-OFDM system, exact channel state information (CSI) is essential. To obtain CSI, several channel estimation algorithms were implemented in Gaussian noise environments. However, real wireless communication environments can be described by non-Gaussian impulsive noise. A robust adaptive channel estimation algorithm based on the maximum correntropy criterion (MCC) learning algorithm is proposed in this paper for a MIMO-OFDM communication system that operates in non-Gaussian impulsive noise environments. The proposed learning algorithm enables considerable improvement in the precision of mean square deviation (MSD) learning performance and in symbol error rate (SER) performance compared with the traditional least mean square (LMS) learning algorithm.

Paper URL