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Ehab AbdulRazzaq Hussein

University of Babylon

Author-ID : 2374240

Computer Science & IT Electrical & Electronics Engineering

Published : 6 Documents Claim Missing Document

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Articles

Fuel Station Monitoring and Automation based on WSN Ehab AbdulRazzaq Hussein; Mahran Obaid Waheed
International Journal of Electrical and Computer Engineering (IJECE) Vol 8, No 5: October 2018
Publisher : Institute of Advanced Engineering and Science

The Iraqi fuel station still now uses old technologies to control its activities from filling tanks to the filling cars. Automate the activity of fuel station is the objective of this work. The aims of fuel station automation are to save the fuel quantities and qualities supplied in fuel station, and to keep the fuel station, the worker and its main parts safe. This work uses the national instrument wireless sensor network (NI WSN). The NI WSN used to automate the protection system and level controlling system which makes the fuel station work under normal ambient temperature, and normal protection conditions. Automation based on a wireless sensor network gives excellent capabilities to automate and monitor fuel station. Through the user interface window the user monitor the status of actuators, protection system controller messages, fuel levels, water level, environment temperature, power source and its quality. The soft controller developed was built within The LABVIEW environment. The results of controller give the desired action through "on" and “off” states of the actuators.

Enhancing the BER and ACLR for the HPA Using Pre-Distortion Technique Ehab AbdulRazzaq Hussein
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 4: August 2019
Publisher : Institute of Advanced Engineering and Science

Power amplifiers are key components in wireless transceivers. Their function is to amplify signal and generate the required Radio Frequency (RF) power that allows to transmit the signal over an appropriate range. The Orthogonal Frequency Division Multiplexing (OFDM) systems are highly sensitive to nonlinear distortion introduced by High Power Amplifier (HPA). The HPA nonlinearity causes in-band and out-of-band distortions. The linearization techniques are used to compensate the nonlinear effects of the high power amplifier. These techniques correct the distortion effects resulting from nonlinearities in the transmitted signal. Many linearization techniques have been developed to improve power amplifier linearity and to decrease both Bit Error Rate (BER) and Adjacent Channel Leakage Ratio (ACLR). This work is set to run the high power amplifier in the nonlinear region. It is also attempting to analyze the resulting signal in terms of the BER and ACLR, next employs pre-distortion linearization techniques to reduce the distortion introduced in this region. According to Digital Video Broadcasting-Terrestrial (DVB-T) standard the linearization techniques, circuit and the OFDM transmitter and receiver is designed and implemented through using computer simulation of AWR Design Environment.

Four dimensional hyperchaotic communication system based on dynamic feedback synchronization technique for image encryption systems Hayder Mazin Makki Alibraheemi; Qais Al-Gayem; Ehab AbdulRazzaq Hussein
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 1: February 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i1.pp957-965

This paper presents the design and simulation of a hyperchaotic communication system based on four dimensions (4D) Lorenz generator. The synchronization technique that used between the master/transmitter and the slave/receiver is based on dynamic feedback modulation technique (DFM). The mismatch error between the master dynamics and slave dynamics are calculated continuously to maintain the sync process. The information signal (binary image) is masked (encrypted) by the hyperchaotic sample x of Lorenz generator. The design and simulation of the overall system are carried out using MATLAB Simulink software. The simulation results prove that the system is suitable for securing the plain-data, in particular the image data with a size of 128×128 pixels within 0.1 second required for encryption, and decryption in the presence of the channel noise. The decryption results for gray and colored images show that the system can accurately decipher the ciphered image, but with low level distortion in the image pixels due to the channel noise. These results make the proposed cryptosystem suitable for real time secure communications.

Detection of electrocardiogram QRS complex based on modified adaptive threshold Ehab AbdulRazzaq Hussein; Ali Shaban Hassooni; Hilal Al-Libawy
International Journal of Electrical and Computer Engineering (IJECE) Vol 9, No 5: October 2019
Publisher : Institute of Advanced Engineering and Science

It is essential for medical diagnoses to analyze Electrocardiogram (ECG signal). The core of this analysis is to detect the QRS complex. A modified approach is suggested in this work for QRS detection of ECG signals using existing database of arrhythmias. The proposed approach starts with the same steps of previous approaches by filtering the ECG. The filtered signal is then fed to a differentiator to enhance the signal. The modified adaptive threshold method which is suggested in this work, is used to detect QRS complex. This method uses a new approach for adapting threshold level, which is based on statistical analysis of the signal. Forty-eight records from an existing arrhythmia database have been tested using the modified method. The result of the proposed method shows the high performance metrics with sensitivity of 99.62% and a positive predictivity of 99.88% for QRS complex detection.

A high security and noise immunity of speech based on double chaotic masking Ehab AbdulRazzaq Hussein; Murtadha K. Khashan; Ameer K. Jawad
International Journal of Electrical and Computer Engineering (IJECE) Vol 10, No 4: August 2020
Publisher : Institute of Advanced Engineering and Science

It is known that increasing the security of the information and reducing the noise effect through public channels are two of the main priorities in developing any communication system. In this article, an efficient, secure communication system with two levels of encryption has been applied to the speech signal. The suggested security approach was implemented by using two different stages of chaotic masking on the signal; one masking was conducted by using Lorenz system and the other masking was built by using Rӧssler chaotic flow system. The main goal of developing this two-chaotic masking approach is to increase the key space and the security of the information. Also, an immunity technique has been implemented in the suggested approach to reduce the noise effect. For practical application purposes, this system was tested with additive white gaussian noise (AWGN) channel. The simulation results show that the quality of reconstructed speech signal is changeable according to the used signal to noise ratio (SNR); therefore, a proposed technique based on digital processing method (DPM) was applied to the first masked signal by converting the sampled data from the analog to the binary format. The simulation results show that an 22 dB (SNR) is sufficient to recover the speech signal with minimum noise by using the suggested approach.

Low-complex Bayesian estimator for imperfect channels in massive muti-input multi-output system Ahmed Hussein Shatti; Ehab AbdulRazzaq Hussein
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 6: December 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i6.pp6261-6271

Motivated by the fact that the complexity of the computations is one of the main challenges in large multiple input multiple output systems, known as massive multiple-input multiple-output (MIMO) systems, this article proposes a low-complex minimum mean squared error (MMSE) Bayesian channel estimator for uplink channels of such systems. First, we have discussed the necessity of the covariance information for the MMSE estimator and how their imperfection knowledge can affect its accuracy. Then, two reduction phases in dimension and floating-point operations have been suggested to reduce its complexity: in phase 1, eigenstructure reduction for channel covariance matrices is implemented based on some truncation rules, while in phase 2, arithmetic operations reduction for matrix multiplications in the MMSE equation is followed. The proposed procedure has significantly reduced the complexity of the MMSE estimator to the first order O(M), which is less than that required for the conventional MMSE with O(M3) in terms of matrix dimension. It has been shown that the estimated channels using our proposed procedure are asymptotically aligned and serve the same quality as the full-rank estimated channels. Our results are validated by averaging the normalized mean squared error (NMSE) over a length of 500 sample realizations through a Monte Carlo simulation using MATLAB R2020a.

Co-Authors Ahmed Hussein Shatti Ali Shaban Hassooni Ameer K. Jawad Hayder Mazin Makki Alibraheemi Hilal Al-Libawy Mahran Obaid Waheed Murtadha K. Khashan Qais Al-Gayem

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