Free space optical (FSO) communication is a promising solution to deliver the last mile communication and to guarantee a high data rate. However, the performance of FSO links can be significantly degraded by adverse weather conditions. Recently, machine learning algorithms (MLAs) have emerged for robust prediction to optimize the network performance. In this work, the Quality factor (Q) of FSO systems is estimated by means of four MLA models, namely, multi-linear regression, support vector regression, decision tree regression, and random forest regression. The synthetic data is used for training and testing these MLAs models, and several atmosphere conditions are considered with multiple transceivers FSO link system. The results of decision tree and random forest models demonstrated high coefficient of determination (R 2 ) and low mean square error (MSE) as compared to the other models.
Amal A. Algedir, Taissir Y. Elganimi(10-2020)

In this paper, imposing the Hadamard Transform (HDT) on Orthogonal Space-Time Block Codes (OSTBC) schemes using multiple transmit antennas is proposed in order to increase the reliability and improve the error performance of wireless communications. It is referred to as joint Hadamard transform and OSTBC schemes with multiple transmit antennas. However, HDT is used to change the location of constellation points by converting the transmit symbols of OSTBC system, and hence extending the Euclidean distance between transmit symbols for a precise detection. Simulation results demonstrated that increasing the number of transmit antennas in OSTBC systems employing 8-PSK improves the Bit Error Rate (BER) performance as in the case of OSTBC 2×2 scheme where an SNR of about 13.5 dB is required to achieve a BER of 〖10〗^(-6), while only about 7 dB in OSTBC 8×8 scheme is required to obtain the same error probability. It is also demonstrated that imposing the Hadamard criteria on the OSTBC 2×2, 4×4, and 8×8 schemes has showed a performance improvement of about 3 dB, 6 dB and 9 dB, respectively, as compared to the conventional OSTBC systems.
Taissir Y. Elganimi, Marwan B. Elkhoja(4-2019)

Modeling, Specification & Evaluation Language (MOSEL), tool used for the performance and reliability modeling of communication systems, computers, and manufacturing systems, once the system is specified using this language. The modeling language is part of the evaluation environment. Once the system is specified using the language, the evaluation environment takes place by executing the performance analyses of the model, and calculating the steady state probabilities . After this stage, results can be collected in the result file or in graphics mode using the Intermediate Graphical Language (IGL), where the aim of this paper is to give an overview of mosel and to show a real example under windows platform.
wael saleh mohamed abughres, Mohamed Ahmed Ramadan Mgheder, Ahmed B. Abdurrman (8-2017)