Open Access
ARTICLE
Impulsive Noise Cancellation in OFDM System Using Low Density Parity Check
1 Department of Computer Science, University of Wah, Wah Cantt, 47040, Pakistan
2 Balochistan University of Information Technology, Engineering and Management Sciences, Quetta, Balochistan
3 Department of Computer Science, COMSATS University Islamabad, Wah Campus, Pakistan
4 Computer Sciences Department, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Riyadh 11671, Saudi Arabia
5 Department of Computer Science, HITEC University, Taxila, Pakistan
6 College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia
7 Department of ICT Convergence, Soonchunhyang University, Korea
* Corresponding Author: Byeong-Gwon Kang. Email:
Computer Systems Science and Engineering 2023, 46(1), 1265-1276. https://doi.org/10.32604/csse.2023.032861
Received 31 May 2022; Accepted 22 July 2022; Issue published 20 January 2023
Abstract
An effective communication application necessitates the cancellation of Impulsive Noise (IN) from Orthogonal Frequency Division Multiplexing (OFDM), which is widely used for wireless applications due to its higher data rate and greater spectral efficiency. The OFDM system is typically corrupted by Impulsive Noise, which is an unwanted short-duration pulse with random amplitude and duration. Impulsive noise is created by humans and has non-Gaussian characteristics, causing problems in communication systems such as high capacity loss and poor error rate performance. Several techniques have been introduced in the literature to solve this type of problem, but they still have many issues that affect the performance of the presented methods. As a result, developing a new hybridization-based method is critical for accurate method performance. In this paper, we present a hybrid of a state space adaptive filter and an information coding technique for cancelling impulsive noise from OFDM. The proposed method is also compared to Least Mean Square (LMS), Normalized Least Mean Square (NLMS), and Recursive Least Square (RLS) adaptive filters. It has also been tested using the binary phase-shift keyed (BPSK), four quadrature amplitude modulation (QAM), sixteen QAM, and thirty-two QAM modulation techniques. Bit error Rate (BER) simulations are used to evaluate system performance, and improved performance is obtained. Furthermore, the proposed method is more effective than recent methods.Keywords
Cite This Article
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.