فهرست مطالب

International Journal Information and Communication Technology Research
Volume:13 Issue: 1, Winter 2021

  • تاریخ انتشار: 1400/10/01
  • تعداد عناوین: 6
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  • Mahmood Rafaei Booket*, Mostafa Mousavi Pages 1-7

    We present a new phase realization approach applied to design the broadband single-layer reflectarray antennas. Such an optimization technique minimizes the adverse effects of frequency dispersion which limit the bandwidth of reflectarray antenna designed by traditional methods. Using this new approach leads to obtaining a wideband reflectarray by finding the optimum element arrangement on the antenna aperture. The excellence of such an approach in comparison with its counterparts is to decrease the dependency of wideband reflectarray design to the element phase behavior. For really assessment this phase synthesis approach, a single-layer reflectarray compromising of square patches loaded with split rings is designed with the help of this optimization technique. It is analytically and numerically shown that the simulated reflectarray can be a broadband antenna in which Side Lobe Level (SLL) value is reduced. To validate the obtained numerical results, a designed 29×29cm2 reflectarray is fabricated and measured. Measurements demonstrate 1.5dB gain bandwidth of about 28% covering 12-16GHz frequency band. Its |SLL| is also less than -17dB (<-13.5dB for uniform excitation arrays). Such a design technique is applicable for approximately all reflectarray elements and relieves the designer from complex elements and multilayer structures.

    Keywords: Reflectarray Antenna, Broadband, Phase Realization Technique, Optimization
  • Zahra Mehrzad, Gholamreza Moradi*, Ayaz Ghorbani Pages 8-18

    This article presents a novel 4×8 SIW Butler matrix (BM) with sidelobe level (SLL) suppression. The BM operates at 60 GHz and is implemented with a new design to achieve a compact size, which would be attractive for future mmWave wireless systems. This beamforming network uses straight SIW phase shifters with two apertures or two metal posts to pursue a smaller circuit area than with curved line phase shifters. Using a stepwise procedure and analyzing the design equations, the crossover and other components of the BM are also designed and optimized. The reflection and isolation coefficients are lower than -10 dB for all input ports and insertion loss magnitude imbalance is below 2.4 dB within the band from 57 GHz to 67 GHz. The slot array antenna fed by the BM shows an SLL lower than -21 dB for inputs 1 and 4 and lower than -14.5 dB for inputs 2 and 3 and provides beam switching

    Keywords: Beamforming network (BFN), 4×8 Butler matrix, Substrate Integrated Waveguide (SIW), Sidelobe level (SLL), millimeter-wave
  • Fereshteh Salimian Rizi, Abolfazl Falahati* Pages 19-24

    This study aims to examine the effective rate of a Multiple-Input Single-Output (MISO) system under independent and non-identical (i.n.i.d) distribution with the Extended Generalized-K (EGK) fading channel. The Moment Generating Function (MGF)-based method is used since it has a computational advantage over probability density function (PDF)-based methods and leads to a whole closed-form relation. Moreover, the H-function EGK distribution is employed to calculate the exact and asymptotic expression for the effective rate of MISO wireless communication system. Finally, the Monte Carlo simulation results, along with accurate and asymptotic results, are presented.

    Keywords: Multi-Input Single-Output (MISO) system, Extended Generalized-K (EGK), effective rate
  • Nasser Sadeghi, Masoumeh Azghani* Pages 25-31

    In order to exploit the advantages of the massive MIMO systems, it is vital to apply the channel estimation task. The huge number of antennas at the base station of a massive MIMO system produces a large set of channel paths which requires to be estimated. Therefore, the channel estimation in such systems is more troublesome. In this paper, we propose to leverage the temporal joint sparsity of the massive MIMO channels to offer a more accurate channel estimation. To attain this goal, we would model the problem to exploit the spatial correlation among different antennas of the BS as well as the inter-user similarity of the channel supports.  In addition, by assuming a slow time-varying channel, the supports of the channel matrices of various snapshots would be equal which enables us to impose the temporal joint sparsity on the channel submatrices. The simulation results validate the efficiency and superiority of the suggested scheme over its rivals

    Keywords: ‎Massive MIMO‎, ‎Channel estimation‎, ‎Sparisity‎, ‎Joint sparsity
  • Fereidoon Rezaei, Mohammadali Afsharkazemi*, Mohammadali Keramati Pages 32-39

     Detection of attacks and anomalies is one of the new challenges in promoting e-commerce technologies. Detecting anomalies of a network and the process of detecting destructive activities in e-commerce can be executed by analyzing the behavior of network traffic. Data mining systems/techniques are used extensively in intrusion detection systems (IDS) in order to detect anomalies. Reducing the size/dimensions of features plays an important role in intrusion detection since detecting anomalies, which are features of network traffic with high dimensions, is a time-consuming process. Choosing suitable and accurate features influences the speed of the proposed task/work analysis, resulting in an improved speed of detection. The present papers utilize a neural network for deep learning to detect e-commerce attacks and anomalies of e-commerce systems. Overfitting is a common event in multi-layer neural networks. In this paper, features are reduced by the firefly algorithm (FA) to avoid this effect. Simulation results illustrate that a neural network system performs with high accuracy using feature reduction. Ultimately, the neural network structure is optimized by using particle swarm optimization (PSO) to increase the accuracy of attack detection capability.

    Keywords: Firefly Algorithm, Attack Detection, Neural Network, PSO Algorithm
  • Mehdi Reza Shahabi, Mehdi Rezaei, Farahnaz Mohanna* Pages 40-49

    E-commerce plays an important role in the world economy. A wide variety of websites have been designed to provide the ability of searching different types of products. Carpet is such a product which cannot be addressed easily with a special code in markets due to the huge variety in its specifications such as layout, color, and texture. This paper introduces a content-based image retrieval system for carpet e-commerce application. This system helps development of the carpet e-commerce where an image can be used instead of any tags including codes or models. An image database containing various Persian carpet images is also made for this application. Furthermore, several content-based image retrieval methods are studied and applied on the carpet database and inspiring by the evaluation results, two methods, QCLD and DCDIP are proposed for carpet e-commerce application. Simulation results show 3.1% and 2.3% decrease on the ANMRR value for the proposed QCLD and DCDIP methods respectively. Retrieval running times also are reported 2.84 and 8.15 seconds for the QCLD and DCDIP methods. In overall, these results reflect higher retrieval performance for the proposed methods.

    Keywords: Content-based image retrieval, Tag-based image retrieval, Carpet e-commerce, Image partitioning, Feature extraction