• List of Articles


      • Open Access Article

        1 - Multiple Antenna Relay Beamforming for Wireless Peer to Peer Communications
        Mohammad Hossein Golbon Haghighi Behrad Mahboobi مهرداد اردبیلی پور
        This paper deals with optimal beamforming in wireless multiple-input-multiple-output (MIMO) relay networks that involves multiple concurrent source-destination pairs with imperfect channel state information (CSI) at the relays. Our aim is the optimization of the MIMO re Full Text
        This paper deals with optimal beamforming in wireless multiple-input-multiple-output (MIMO) relay networks that involves multiple concurrent source-destination pairs with imperfect channel state information (CSI) at the relays. Our aim is the optimization of the MIMO relay weights that minimize the total relay transmit power subject to signal-to-interference-plus-noise ratio (SINR) of all destinations to be kept above a certain threshold. Since power minimization is a non-convex quadratically constrained quadratic programming (QCQP), we use semi-definite programming (SDP) relaxation of above mentioned problem by using a randomization technique. Numerical Monte Carlo simulations verify the performance gain of our proposed multiple antenna relay system in terms of transmit power and symbol error probability. Manuscript Document
      • Open Access Article

        2 - Parameter Estimation in Hysteretic Systems Based on Adaptive Least-Squares
        Mansour Peimani Mohammad Javad Yazdanpanah Naser Khaji
        In this paper, various identification methods based on least-squares technique to estimate the unknown parameters of structural systems with hysteresis are investigated. The Bouc-Wen model is used to describe the behavior of hysteretic nonlinear systems. The adaptive ve Full Text
        In this paper, various identification methods based on least-squares technique to estimate the unknown parameters of structural systems with hysteresis are investigated. The Bouc-Wen model is used to describe the behavior of hysteretic nonlinear systems. The adaptive versions are based on the fixed and variable forgetting factor and the optimized version is based on optimized adaptive coefficient matrix. Simulation results show the efficient performance of the proposed technique in identification and tracking of hysteretic structural system parameters compared with other least square based algorithms. Manuscript Document
      • Open Access Article

        3 - Digital Video Stabilization System by Adaptive Fuzzy Kalman Filtering
        Mohammad javad Tanakian Mehdi Rezaei Farahnaz Mohanna
        Digital video stabilization (DVS) allows acquiring video sequences without disturbing jerkiness, removing unwanted camera movements. A good DVS should remove the unwanted camera movements while maintains the intentional camera movements. In this article, we propose a no Full Text
        Digital video stabilization (DVS) allows acquiring video sequences without disturbing jerkiness, removing unwanted camera movements. A good DVS should remove the unwanted camera movements while maintains the intentional camera movements. In this article, we propose a novel DVS algorithm that compensates the camera jitters applying an adaptive fuzzy filter on the global motion of video frames. The adaptive fuzzy filter is a Kalman filter which is tuned by a fuzzy system adaptively to the camera motion characteristics. The fuzzy system is also tuned during operation according to the amount of camera jitters. The fuzzy system uses two inputs which are quantitative representations of the unwanted and the intentional camera movements. Since motion estimation is a computation intensive operation, the global motion of video frames is estimated based on the block motion vectors which resulted by video encoder during motion estimation operation. Furthermore, the proposed method also utilizes an adaptive criterion for filtering and validation of motion vectors. Experimental results indicate a good performance for the proposed algorithm. Manuscript Document
      • Open Access Article

        4 - Camera Identification Algorithm Based on Sensor Pattern Noise Using Wavelet Transform, SVD / PCA and SVM Classifier
        Kimia Bolouri Mehdi Javanmard Mohammad Firouzmand
        Identifying the source camera of an image is one of the most important issues of digital court and is useful in many applications, such as images that are presented in court as evidence. In many methods, the image noise characteristics, extraction of Sensor Pattern Nois Full Text
        Identifying the source camera of an image is one of the most important issues of digital court and is useful in many applications, such as images that are presented in court as evidence. In many methods, the image noise characteristics, extraction of Sensor Pattern Noise and its correlation with non-uniformity of the light response (PNU) are used. In this paper we have presented a method based on photo response non uniformity (PRNU) that provides some features for classification by support vector machine (SVM). Because the noise model is affected by the complexity of the image, we used the wavelet transform to de-noise and reduce edge effects in PRNU noise pattern and also raise the detection accuracy. We also used the Precision processing theory to reduce the image size, then we simplified and summarized the data using the Single Value Decomposition (SVD) Or principal component analysis (PCA). The results show that using two-level wavelet transform and summarized data is more suitable using PCA. Manuscript Document
      • Open Access Article

        5 - Video Transmission Using New Adaptive Modulation and Coding Scheme in OFDM based Cognitive Radio
        Hassan Farsi Farid Jafarian
        As Cognitive Radio (CR) used in video applications, user-comprehended video quality practiced by secondary users is an important metric to judge effectiveness of CR technologies. We propose a new adaptive modulation and coding (AMC) scheme for CR, which is OFDM based sy Full Text
        As Cognitive Radio (CR) used in video applications, user-comprehended video quality practiced by secondary users is an important metric to judge effectiveness of CR technologies. We propose a new adaptive modulation and coding (AMC) scheme for CR, which is OFDM based system that is compliant with the IEEE.802.16. The proposed CR alters its modulation and coding rate to provide high quality system. In this scheme, CR using its ability to consciousness of various parameters including knowledge of the white holes in the channel spectrum via channel sensing, SNR, carrier to interference and noise ratio (CINR), and Modulation order Product code Rate (MPR) selects an optimum modulation and coding rate. In this scheme, we model the AMC function using Artificial Neural Network (ANN). Since AMC is naturally a non-liner function, ANN is selected to model this function. In order to achieve more accurate model, Genetic algorithm (GA) and Particle Swarm Optimization (PSO) are selected to optimize the function representing relationship between inputs and outputs of ANN, i.e., AMC model. Inputs of ANN are CR knowledge parameters, and the outputs are modulation type and coding rate. Presenting a perfect AMC model is advantage of this scheme because of considering all impressive parameters including CINR, available bandwidth, SNR and MPR to select optimum modulation and coding rate. Also, we show that in this application, GA rather than PSO is better choice for optimization algorithm. Manuscript Document
      • Open Access Article

        6 - EBG Structures Properties and their Application to Improve Radiation of a Low Profile Antenna
        Masoumeh Rezaei Abkenar Pejman Rezaei
        In this paper we have studied the characteristics of mushroom-like Electromagnetic Band Gap (EBG) structure and performance of a low profile antenna over it. Afterward, a novel EBG surface is presented by some modifications in mushroom-like EBG structure. This structure Full Text
        In this paper we have studied the characteristics of mushroom-like Electromagnetic Band Gap (EBG) structure and performance of a low profile antenna over it. Afterward, a novel EBG surface is presented by some modifications in mushroom-like EBG structure. This structure, which has more compact electrical dimensions, is analyzed and its electromagnetic properties are derived. Results show that resonant frequency of this novel structure is about 15.3% lower than the basic structure with the same size. Moreover, the novel EBG structure has been used as the ground plane of antenna. Its application has improved radiation of a low profile dipole antenna. The antenna performance over the new EBG ground plane is compared with the conventional mushroom-like EBG structure. Simulation results show that using this slot loaded EBG surface, results in 13.68dB improvement in antenna return loss, in comparison with conventional mushroom-like EBG, and 33.87dB improvement in comparison with metal ground plane. Besides, results show that, EBG ground planes have increased the input match frequency bandwidth of antenna. Manuscript Document
      • Open Access Article

        7 - A New Approach to Overcome the Count to Infinity Problem in DVR Protocol Based on HMM Modelling
        Mehdi Golestanian Reza Ghazizadeh
        Due to low complexity, power and bandwidth saving Distance Vector Routing has been introduced as one of the most popular dynamic routing protocol. However, this protocol has a serious drawback in practice called Count To Infinity problem or slow convergence. There are m Full Text
        Due to low complexity, power and bandwidth saving Distance Vector Routing has been introduced as one of the most popular dynamic routing protocol. However, this protocol has a serious drawback in practice called Count To Infinity problem or slow convergence. There are many proposed solutions in the literature to solve the problem, but all of these methods depend on the network topology, and impose much computational complexity to the network. In this paper, we introduce a new approach to solve the Count To Infinity using hidden markov model (HMM), which is one of the most important machine learning tools. As the modelling results show, the proposed method is completely independent from the network topology and simple with low computational complexity. Manuscript Document