In this paper, a customized Auto-Encoder Complex Valued Convolutional Neural Network (AE-CV-CNN) that has been developed in a prior work is applied to Single Symbol Generalized Spatial Modulation (SS-GSM) scheme with new extracted features. The achieved reductions in the computational complexity at the receiver is at least 63.64% for M-PSK schemes compared to the complexity of Maximum Likelihood (ML) detection algorithm. This Fast detection algorithm is based on a proposed Low Complexity ML (LC-ML) detector that affords a complexity reduction of at least 40.91%. With these proposed algorithms, the complexity is reduced as the spatial constellation size increases. Furthermore, in comparison to other sub optimal detection algorithms, the computational complexity in terms of real valued multiplications of the AE-CV-CNN applied to LC-ML is independent of the spatial spectrum efficiency which means that the total spectrum efficiency increases with larger spatial constellation size at no additional complexity.
Akram A. Marseet , Taissir Y. Elganimi(10-2019)

The introduction of new services with different bandwidth requirements, e.g., data and multimedia, to cellular mobile radio networks makes many of the traditional mechanisms unusable or less efficient. The call admission control and the handover handling are the most sensitive issues to this extension. The performance of all services including the traditional voice and the new services can be dramatically effected if no appropriate schemes are used. In this research work, a new call admission and handover handling schemes for a cellular mobile network that offers two service types: voice and data is proposed. The data connections are assumed to be transmitted at different data rates, which are an integer multiple to that of one traffic channels, which are full speed(Cd1) & reduced peed(Cd2). In order to reduce the handover failure probability of data connections, the data mobile terminals (MT) are assumed to have the capability of transmitting at two different data rates. If the handover request can not be satisfied by the base station of the destination cell due to unavailable free traffic channels, the data mobile terminals tries with a lower data rate. The handover fails if the network is incapable on providing the minimum data rate at which the mobile terminal can transmit. The reduced data connection or data rate can be speeded up to full data rate or full speed as soon as enough bandwidth is available. The effect of different traffic and configuration parameters on the performance of the different models for two cell model with equal input traffic intensity, two cell model with different input traffic intensity, and two cell model with equal input traffic intensity considering the congestion rate for the highway model are studied as the models of this research. These models are built using MOSEL language (Modeling Specification and Evaluation Language). The results of investigating the mentioned models showed the effect of the handover, and speed of data on these different models.
W. ABUGHRES(1-2000)

A performance evaluation of sound recognition techniques in recognizing some spoken Arabic words, namely digits from zero to nine, is proposed. One of the main characteristics of all Arabic digits is polysyllabic words except for zero. The performance analysis is based on different features of phonetic isolated Arabic digits. The main aim of this paper is to compare, analyze, and discuss the outcomes of spoken Arabic digits recognition systems based on three recognition features: the Yule-Walker spectrum features, the Walsh spectrum features, and the Mel frequency Cepstral coefficients (MFCC) features. The MFCC based recognition system achieves the best average correct recognition. On the other hand, the Yule-Walker based recognition system achieves the worst average correct recognition. arabic 7 English 60
A. Ganoun, I. Almerhag(6-2012)