Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing

Phase noise is a random unwanted variation interfered with Orthogonal Frequency Division Multiplexing (OFDM) signal according to many factors. One of the important factor is related to oscillator itself which generates the carrier signals and causes Inter Channel Interference Noise (ICI). The sec...

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Main Author:	Alsaadi, Alaa Abdullah Mohammed
Format:	Thesis
Language:	English
Published:	2020
Subjects:	Wireless communication systems Orthogonal frequency division multiplexing
Online Access:	http://psasir.upm.edu.my/id/eprint/90780/1/FSKTM%202020%2018%20IR.pdf
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spelling	my-upm-ir.907802021-09-27T03:38:03Z Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing 2020-02 Alsaadi, Alaa Abdullah Mohammed Phase noise is a random unwanted variation interfered with Orthogonal Frequency Division Multiplexing (OFDM) signal according to many factors. One of the important factor is related to oscillator itself which generates the carrier signals and causes Inter Channel Interference Noise (ICI). The second main factor is a multipath fading channel which causes a delay in OFDM signal and results for Inter Symbol Interference Noise (ISI).Basically, phase noise is considered as main problem that causes significant degradation in detecting packet-based OFDM signals. Therefore, its estimation is essential to reduce the interference among other subcarrier signals. The main objective of this thesis is to develop a new technique for phase noise, accuracy and complexity in OFDM signal. This technique is called Projected Quadratic Majorized Covariance Correlation (PQMCC) technique. PQMCC technique is proposed to reduce the power of noise in OFDM signal, arise the accuracy of received signal and decrease the complexity. Precisely, by proposing the projected signal (py>) in PQMCC technique has solved the three main issues: power of noise, accuracy in received random signal (y>) and complexity in Tight Quadratic Majorization algorithm (TQM) for Phase Noise Estimation Technique. PQMCC Technique is simulated in MATLAB. The simulation results shows that the Wiener Process Phase Noise (PHN) has no effect over the proposed signal (py>) since it utilizes the properties of orthogonal projection matrix which leads to preserve data [theta (θ) and vectors (h)] from destruction of noise. Literally, the power of noise is reduced from 69dB (7.8458e+06Hz) to 67.2dB (5.2069e+06Hz) when signal to noise ratio (snr) is 15dB. Moreover, the accuracy of the proposed projected signal (py>) is proven when the sinusoidal signal shows right angle (θ=90°) and the area of recovered projected signal (py>) is reduced by around 46.2891% in cm2 comparing with random signal (y>) in TQM algorithm. In addition to that, by proposing the projected signal (py>) in PQMCC technique, complexity of TQM algorithm is reduced from second order of big notation O(Nc2) to first order O(Nc).In summary, the outcome of PQMCC technique based on noise attenuation, accuracy, and complexity reduction has achieved and proven in this thesis. Wireless communication systems Orthogonal frequency division multiplexing 2020-02 Thesis http://psasir.upm.edu.my/id/eprint/90780/ http://psasir.upm.edu.my/id/eprint/90780/1/FSKTM%202020%2018%20IR.pdf text en public masters Universiti Putra Malaysia Wireless communication systems Orthogonal frequency division multiplexing Latip, Rohaya
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
advisor	Latip, Rohaya
topic	Wireless communication systems Orthogonal frequency division multiplexing
spellingShingle	Wireless communication systems Orthogonal frequency division multiplexing Alsaadi, Alaa Abdullah Mohammed Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing
description	Phase noise is a random unwanted variation interfered with Orthogonal Frequency Division Multiplexing (OFDM) signal according to many factors. One of the important factor is related to oscillator itself which generates the carrier signals and causes Inter Channel Interference Noise (ICI). The second main factor is a multipath fading channel which causes a delay in OFDM signal and results for Inter Symbol Interference Noise (ISI).Basically, phase noise is considered as main problem that causes significant degradation in detecting packet-based OFDM signals. Therefore, its estimation is essential to reduce the interference among other subcarrier signals. The main objective of this thesis is to develop a new technique for phase noise, accuracy and complexity in OFDM signal. This technique is called Projected Quadratic Majorized Covariance Correlation (PQMCC) technique. PQMCC technique is proposed to reduce the power of noise in OFDM signal, arise the accuracy of received signal and decrease the complexity. Precisely, by proposing the projected signal (py>) in PQMCC technique has solved the three main issues: power of noise, accuracy in received random signal (y>) and complexity in Tight Quadratic Majorization algorithm (TQM) for Phase Noise Estimation Technique. PQMCC Technique is simulated in MATLAB. The simulation results shows that the Wiener Process Phase Noise (PHN) has no effect over the proposed signal (py>) since it utilizes the properties of orthogonal projection matrix which leads to preserve data [theta (θ) and vectors (h)] from destruction of noise. Literally, the power of noise is reduced from 69dB (7.8458e+06Hz) to 67.2dB (5.2069e+06Hz) when signal to noise ratio (snr) is 15dB. Moreover, the accuracy of the proposed projected signal (py>) is proven when the sinusoidal signal shows right angle (θ=90°) and the area of recovered projected signal (py>) is reduced by around 46.2891% in cm2 comparing with random signal (y>) in TQM algorithm. In addition to that, by proposing the projected signal (py>) in PQMCC technique, complexity of TQM algorithm is reduced from second order of big notation O(Nc2) to first order O(Nc).In summary, the outcome of PQMCC technique based on noise attenuation, accuracy, and complexity reduction has achieved and proven in this thesis.
format	Thesis
qualification_level	Master's degree
author	Alsaadi, Alaa Abdullah Mohammed
author_facet	Alsaadi, Alaa Abdullah Mohammed
author_sort	Alsaadi, Alaa Abdullah Mohammed
title	Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing
title_short	Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing
title_full	Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing
title_fullStr	Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing
title_full_unstemmed	Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing
title_sort	projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing
granting_institution	Universiti Putra Malaysia
publishDate	2020
url	http://psasir.upm.edu.my/id/eprint/90780/1/FSKTM%202020%2018%20IR.pdf
_version_	1747813658129334272

Projected majorized-correlation technique for noise filtering and accuracy in orthogonal frequency division multiplexing

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