International Conference on Computer and Knowledge Engineering

Home / 13th International Conference on Computer and Knowledge Engineering

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

Authors :

Mojtaba Hajiabadi¹

1- Faculty of Electrical and Computer Engineering, University of Birjand, Iran

Keywords :

Machine learning،least mean square،maximum correntropy criterion،MIMO-OFDM system،adaptive filter،impulsive noise

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.

Papers List

List of archived papers

LightFedSelect: A Lightweight Framework for Byzantine-Robust Federated Learning

Seyed Saeed Razavi - Seyed Arsalan Vasegh Rahim Parvar - Soroosh Dadashi Pakdeh - Mohammad Matin Rezaeifard - Morteza Mollaie Chafi - Reza Ebrahimi Atani

Token-Based Access Control for Inter-organization Collaboration in Hyperldger Fabric

Parsa Hedayatnia - Mohammad Ata Jalilian - Mohammad Allahbakhsh - Haleh Amintoosi