IRMA-International.org: Creator of Knowledge
Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

BER Improvement in OFDM Systems Using Wavelet Transform Based on Kalman Filter

BER Improvement in OFDM Systems Using Wavelet Transform Based on Kalman Filter
View Sample PDF
Author(s): Sajjan Singh (CGC Technical Campus, Jhanjeri, India)
Copyright: 2020
Pages: 23
Source title: Fundamental and Supportive Technologies for 5G Mobile Networks
Source Author(s)/Editor(s): Sherine Mohamed Abd El-Kader (Electronics Research Institute, Egypt)and Hanan Hussein (Electronics Research Institute, Egypt)
DOI: 10.4018/978-1-7998-1152-7.ch005

Purchase

View BER Improvement in OFDM Systems Using Wavelet Transform Based on Kalman Filter on the publisher's website for pricing and purchasing information.

Abstract

Orthogonal frequency division multiplexing (OFDM) is an efficient method of data transmission for high speed communication systems over multipath fading channels. However, the peak-to-average power ratio (PAPR) is a major drawback of multicarrier transmission systems such as OFDM is the high sensitivity of frequency offset. The bit error rate analysis (BER) of discrete wavelet transform (DWT)-OFDM system is compared with conventional fast Fourier transform (FFT)-OFDMA system in order to ensure that wavelet transform based OFDMA transmission gives better improvement to combat ICI than FFT-based OFDMA transmission and hence improvement in BER. Wavelet transform is applied together with OFDM technology in order to improve performance enhancement. In the proposed system, a Kalman filter has been used in order to improve BER by minimizing the effect of ICI and noise. The obtained results from the proposed system simulation showed acceptable BER performance at standard SNR.

Related Content

Dina Darwish. © 2024. 43 pages.
Kassim Kalinaki, Musau Abdullatif, Sempala Abdul-Karim Nasser, Ronald Nsubuga, Julius Kugonza. © 2024. 23 pages.
Yogita Yashveer Raghav, Ramesh Kait. © 2024. 17 pages.
Renuka Devi Saravanan, Shyamala Loganathan, Saraswathi Shunmuganathan. © 2024. 21 pages.
Veera Talukdar, Ardhariksa Zukhruf Kurniullah, Palak Keshwani, Huma Khan, Sabyasachi Pramanik, Ankur Gupta, Digvijay Pandey. © 2024. 30 pages.
Dharmesh Dhabliya, Sukhvinder Singh Dari, Nitin N. Sakhare, Anish Kumar Dhablia, Digvijay Pandey, Balakumar Muniandi, A. Shaji George, A. Shahul Hameed, Pankaj Dadheech. © 2024. 9 pages.
Avtar Singh, Shobhana Kashyap. © 2024. 11 pages.
Body Bottom