Mohamed H. Essai

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The multiuser asymptotically robust invariant demodulation algorithm for CDMA systems is considered. It provides multiple access interference (MAI) suppression and does not require controlling of power of mobile transmitters. In addition, the algorithm provides high quality demodulation under the conditions of non-Gaussian noise. The algorithm(More)
The most commonly used multiple access technique in wireless communication sphere is the direct sequence code division multiple access. The main drawback of this system is multiple access interference (MAI) caused by sharing a number of users the same channel. Multiuser Detection enhances the performance of DS-CDMA system by combating MAI. In this paper,(More)
The effect of increasing the number of transmit and receive antennas in Spatial Multiplexing - Multiple Input Multiple Output (MIMO) communication systems, on the performance of LTE detectors, was investigated, in order to get more robust detectors. The channel environments used are Additive White Gaussian (AWGN), noise and heavy-tailed noise distributions(More)
This paper introduces, a threedimensional (3D) neural network electric fields estimator, which will be used to determine the electric field distribution on high voltage insulator surface. A 15 KV composite suspension insulator has been used. In the course of collection the training data sets the finite element method (FEM) have been used. The collected/used(More)
Based on the use of Fair M-Estimator, Fair robust detection algorithm was introduced, in order to get more robust detector. The proposed algorithm designed for LTE communication networks, which use spatial multiplexing transmission method, in Multiple Input Multiple Output systems. The channel environments used are Additive White Gaussian (AWGN) noise and(More)
Multi-layer feed-forward neural networks has been proven to be very successful in many applications, as industrial modeling, classification and function approximations. Training data containing outliers are often a problem for these supervised neural networks learning methods that may not always come up with acceptable performance. Robust neural network(More)
In multiuser detection techniques, the maximum likelihood multiuser detector provides the best performance in DS-CDMA systems with impulsive ambient noise. But the high complexity makes it impractical. And therefore, effective sup-optimal detectors in non-Gaussian noise are needed. In this paper, we present two-layer perceptron neural network with back(More)
Artificial neural networks are one of the most popular and promising areas of artificial intelligence research. Training data containing outliers are often a problem for supervised neural networks learning algorithms that may not always come up with acceptable performance. Many robust learning algorithms have been proposed so far to improve the performance(More)
New adaptive asymptotically robust invariant algorithms are proposed, and examined. These algorithms are used for the detection of signals with some unknown parameters observed in additive noise with unknown distribution. The algorithms are based on asymptotically robust invariant (ARI) algorithms previously developed by the authors. The extended model of(More)