Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

Abstract                                                         

The issue of the protection of the environment is a shared responsibility between several destinations and sectors, and constitutes a main subject in which they can achieve sustainable development. In the sectors of government programs can be set up towards the establishment of the government sector to the green environment, so to be the implementati

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. As more and more information is transacted over wireless media, there has been increasing criminal activity directed against such systems. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. We have studied the performance of differential chaos shift keying (DCSK) with 2×2 Alamouti scheme and 2×1 Alamouti scheme for different chaotic maps over additive white Gaussian noise (

In this study, the behavior of screw piles models with continuous helix was studied by conducting laboratory experimental tests on a single screw pile that has several aspect ratios (L/D) under the influence of static axial compression loads. The screw piles were inserted in a soft soil that has a unit weight of 18.72 kN/m3 and moisture content of 30.19%. Also, the soil has a liquid limit of 55% and a plasticity index of 32%. A physical laboratory model was designed to investigate the ultimate compression capacity of the screw pile and measure the generated porewater pressure during the loading process. The bedding soil was prepared according to the field unit weight and moisture content and the failure load was assumed correspondin

A total of 247 Mallard ( Anas platyrhynchos platyrhynchos L.) from Baghdad and Kut were examined for the Cestodes Diorchis stefanskii Sobolevicanthes gracilis; Hymenolepis mastigopraditae and the Nematode Amidostomum acutum in the first time in Iraq . Among these , 151 birds were found infected by these helminthes It has been found small nodules on the external surface of the intestine , Ulceration of mucosa inflammatory infiltrate , Oedemats changes and hyperplasia in the section of infected intestine were noticed.

      This research is based on  interaction of two most important variables to the business organizations in the current era ,  these two variables are (marketing orientation and quality of service),  this research is trying to urge the service organizations to reconsider the mechanisms adopted in the formulation of its plans, It was the application of research in Korek Telecom and Asia Cell Telecom as a sector of service active and important in the business sector in Iraq, the information was obtained through the design of the Likert questionnaire , it was distributed (92) questionnaire , (50) for the company Korek Telecom and (42) of the Asia-Cell and represent research population sample

Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a

Face Identification is an important research topic in the field of computer vision and pattern recognition and has become a very active research area in recent decades. Recently multiwavelet-based neural networks (multiwavenets) have been used for function approximation and recognition, but to our best knowledge it has not been used for face Identification. This paper presents a novel approach for the Identification of human faces using Back-Propagation Adaptive Multiwavenet. The proposed multiwavenet has a structure similar to a multilayer perceptron (MLP) neural network with three layers, but the activation function of hidden layer is replaced with multiscaling functions. In experiments performed on the ORL face database it achieved a