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Ahmed Hussein Shatti
University of Babylon
Computer Science & IT Electrical & Electronics Engineering

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Automation conditions of mobile base station shelter via cloud and IoT computing applications Ahmed Hussein Shatti; Haider Ali Hasson; Laith Ali Abdul-Rahaim
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4550-4557

Abstract

In this paper, a monitoring and controlling process of the mobile base station shelter has been implemented. We have proposed a model that is based on a firebase cloud service and the principle of the internet of things (IoT) to carry out the process of automation. In this model, we have used Raspberry Pi 4 as the main microcontroller of our system that has interacted with a DHT11 Humidity-Temperature sensor and a PIR motion sensor. It's found that the Pi4 module provides efficient analysis, low consumption of power, and effective control of the operation. It turns ON/OFF the electrical appliances automatically inside the shelter. The main advantage of our proposed model is to maintain the temperature and humidity degrees inside the shelter within the required range of operation. Another important advantage is to diminish the tall human exertion level behind the monitoring process throughout the day. The model has been tested through a localhost server via an HTML page. The last one was created with the assistance of HTML and CSS languages to be used as a local user interface. Moreover, the Raspberry Pi 4 was programmed by Python Language to catch up on the reading of the sensors, processes the data, and sends it to the cloud service. Finally, those data will be shown in real-time to the authenticated user on the database of the firebase cloud service.
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

Abstract

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 Ehab AbdulRazzaq Hussein Haider Ali Hasson Laith Ali Abdul-Rahaim