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, we present an analytical traffic model for the Universal Mobile Telecommunication Systems (UMTS). In 3G networks we have dynamic capacity that depends on the interference levels in the covered area and the number of active users. This implies that the distance of the mobile user from the base station is also an important factor because of the signal fading. The first part of this paper is an algorithm written in c++ programming language that distributes users in different zones assuming that the cell area is virtually divided into Z zones depending on the number of users. The last part of this paper we build a mathematical model of a 3G cell using the above assumption , and to prove, that the product form holds in the case of two cells with uniform and non uniform traffic. By this result more complicated networks can be analyzed, to calculate the performance measures of the network.
WAEL S. ABUGHRES, MIKE E. WOODWARD(6-2006)

Multiple Input Multiple Output (MIMO) systems with limited Radio Frequency (RF) chains play a pivotal role in the Fifth Generation (5G) of wireless networks. However, the transmitter of Generalized Spatial Modulation MIMO (GSM-MIMO) systems that characterized by a single RF chain and multiple active antennas is capable of reducing both the energy consumption and the transmitter cost. In this paper, combining GSM-MIMO systems with the fully digital Geometric Mean Decomposition (GMD)-based precoding scheme and Analog Beamforming (ABF) into Hybrid Beamforming (HBF) regime is presented for Millimeter-wave (mmWave) massive MIMO systems which is a key enabler for 5G networks. In addition, applying the norm-based user selection algorithm in GSM-MIMO scheme with GMD-based hybrid precoding is proposed, and referred to as Multiuser Steered GSM-MIMO (MUS-GSM-MIMO) scheme. Simulation results demonstrate that the proposed schemes are capable of achieving considerable performance gains over the conventional GSM-MIMO schemes, while avoiding the overwhelming costs of multiple RF chains. Therefore, the proposed schemes are very efficient and highly suitable for large-scale and 5G wireless networks.
Taissir Y. Elganimi, Amani A. Aturki(9-2020)