TABRIZ JOURNAL OF ELECTRICAL ENGINEERING
Year:2019 | Volume:49 | Issue:2 (88) |Papers Count:40

In this paper, performance improvement of a direct torque-controlled permanent-magnet synchronous motor drive is achieved through a novel delay dependent controller. The method is based on a delayed sliding controller with exponential reaching law in the outer speed loop combined with a nonlinear feedback linearization based controller in the inner flux and torque loop. Delayed sliding mode controller guarantees fast reaching to the sliding surface and avoids unwanted chattering due to its continuous approximation of the switching term in the sliding law. Simultaneously, the feedback linearization deals with motor nonlinearities and facilitates linear controller design for torque and flux regulation. The proposed scheme is based on the Lyapunov approach and utilizes space vector pulse width modulation with optimized design parameters. It provides fast torque and flux control with diminished fluctuations, high torque at low speed, fast speed response and reduced stator current distortions. Theoretical analysis and simulation results on a Siemens servo motor (1FT7082-AF7) prove the merits of the method in considering flux, torque and speed control performance compared with the conventional direct torque control based methods.

Adaptive algorithms play an important role in order to improve performance of diffusion distributed network. In comparison of diffusion Normalized least mean square algorithm, family of diffusion subband algorithms have faster convergence rate when the input signal is highly correlated. This paper solves the problem of distributed estimation in the diffusion networks based on improved multiband-structured subband adaptive filter (IMSAF) and diffusion improved multiband structured subband adaptive filter (DIMSAF) is established. In proposed algorithm, convergence behavior improved due to using several input projections instead of single vector of input data. In addition, when the projection order is increased, the convergence rate of the proposed algorithm improves. The validity of the DIMSAF in comparison of DLMS, DAPA, VSS-DAPA and DRLS algorithms is demonstrated by several computer simulations. The results show fastest convergence rate.

Nature-inspired algorithms are the imitation of nature opened a new era in calculations for solving optimization problems. In this thesis, we will provide an optimization algorithm inspired by nature using the instinctive behavior of birds. In this thesis, particles learn to have a conditional normal behavior towards an unconditioned stimulus using the classical conditioning learning behavior of birds. Particles will be divided into multiple categories in the problem space. If any particle had a low-level category, it will try to move towards its best personal experience. If any particle had a high-level category, it will learn to move towards the global optimum in its category. Using the idea of birds’ sensitivity towards the environment, in which birds are flying, we tried to move particles in incompetent spaces more quickly so that the particle goes far away from that space, and vice versa, we will bring down the particles’ speed in valuable spaces to search for more. We selected a population based on the particles’ merit in the initial population selection using the instinctive behavior of birds. The proposed method was implemented in MATLAB software, and the results have been compared in several different ways. The results showed that the proposed method is a reliable algorithm to solve the static problems.

Nowadays, most of information systems can be modeled as multilayer networks which each layer includes some nodes connected to each other by different types of links. Information diffusion in networks is the subject that researchers considered recently and they analyzed and modeled this process type in the networks. Although most of researches in this field have focused on single layer networks, but in the real world, because of the complexity of relations, most systems must be modeled as multilayer networks. In the previous works, there are much simplification in problem space, like projection all layer into one layer or negligence the mutual effect of nodes in different layers. So a new effective model for analyzing diffusion in multilayer networks is needed. This method is focused on predicting diffusion in multilayer networks, with considering mutual effect of different layers on each other. The most important specification of this proposed method, is the ability to specify power of all layers and measuring this power regardless node's similarity or difference. In fact, this model can determine the diffusion power of each type of nodes. The model is applied on two real bibliographic information networks, and experimentally demonstrated the effectiveness of this model compared with other diffusion models.

In this paper, a two-stage common source low noise amplifier (LNA) with novel input matching network is presented for ultra-wideband (UWB) applications. The proposed input matching network employing the active feedback and an inductive network is proposed to achieve the wideband matching, low noise figure and high flatness gain simultaneously. The proposed LNA has been designed and simulated in the RF-TSMC CMOS 0. 18 μ m technology by Advanced Design System (ADS). The simulation results exhibit a flat power gain (S21) of 15± 1 dB with a noise figure (NF) lower than 3. 5 dB and an input impedance matching less than – 10 dB over 3. 1 to 10. 6 GHz bandwidth. It consumes 10 mW from 1 V supply voltage and occupies 0. 85 mm2.

Resolver is an electromagnetic position sensors. To ensure the performance of the resolver is not deteriorated by the eccentricities, pancake resolvers are employed in industrial applications. The accuracy of pancake resolvers is suspected to be influenced by run-out fault. In this paper, the effect of run-out fault on the accuracy of the wound rotor resolver is studied by 3-D time stepping finite element method (TSFEM). Then, the contribution of the resolver’ s rotor and the secondary of rotary transformer (RT) in the detected error is determined. Based on the analysis, an optimized structure is proposed to decrease the effect of run out fault. Finally, the success of the optimization is validated using experimental tests on the prototype of the sensor.

This paper proposes a new method for the discrete control of active power and stator flux of permanent magnet synchronous generator in wind turbine. The main idea of this method is discrete control of the active power and stator flux from the perspective of the flux and angular load vector and Only by knowing active power and stator flux, the desired stator flux vector for the next moment is predicted. Then in order to generate the reference voltage vector, the space vector modulation is used which stabilizes the switching frequency and reduces the power and flux ripples. In this method all the calculations are done only in the stator reference frame and there is no need for translation to other reference frames. Compared to the vector control, this method has high dynamic response. The rotor flux and several machine parameters, including the stator inductance, are not interfered in the equations, which improves the robustness controller. Also, there is no need for integral proportional controllers and their coefficients adjustment. In this paper, MATLAB software is used for simulations. Comparison of the results of proposed method and vector control method optimized by the particle swarm algorithm, validates the high dynamic response, reduced active power and the stator flux ripple and overshoot in the proposed method.

Alzheimer’ s disease (AD), a progressive, irreversible neurodegenerative disorder, occurs most frequently in older adults and gradually destroys regions of the brain that are responsible for memory, thinking, learning, and behavior. In this paper, AD prediction is investigated based on rs-fMRI and sMRI analysis. Three feature selection algorithms based on soft computing method has been proposed to classify MCI-C from MCI-NC through training SVM. This is the first study used to integrate rs-fMRI and sMRI for AD prediction. The results refer to the significant brain areas (functional and structural) impaired in AD. Furthermore, NBS method on brain functional parcellations has been utilized for separating MCI-C from MCI-NC and detecting the discriminative ability networks for AD prediction.

Audio event detection (AED) is a modern way to collect data about human activities in the workplace or in other life environments. We proposed a novel adaptable model based on using two parameters, α and ᵦ to detect all audio events that may be present in a given record accompanied by their time limits in which they occur. After feature extraction and setting the values of the two key parameters, alpha and beta, the audio sequence will be sent into two distinct sub-systems for event detection. The outputs from the two sub-classifiers are then combined and necessary refinements are made on the event time limits. The final detected events are sent to the KNN classifier. The parameters serve as a trade-off tool between precision and recall expectation in the detection process. In the tests, 16 different audio events of an office room were detected, some being similar to each other and some have very similar characteristics to those of the background noise. At frame-based (FB) level, the precision rate was 70. 1%, the rate of recall was 75. 8%, and F1-measure was 72. 8%. The F1-measure has increased by 10. 8% suggesting promising applications of the model.

In this paper, an approach is proposed for power allocation in Non-orthogonal multiple access (NOMA) systems in downlink to achieve user fairness from user capacity perspective and to optimize transmitter power consumption as well. In recent works, researchers have defined optimization problems and solved them, as in a method called Fair-NOMA, to maximize the capacity of each user in NOMA compared to OMA but the difference between the capacity of users and optimizing the transmitter power consumption are not considered. In this paper, a NOMA system with 2 and more than 2 users in downlink is considered. In the 2-user scenario by equating capacities of users, the Jain fairness index is maximized, fairness is achieved in transmitter power consumption and the difference between the capacities of users is eliminated. In addition, computer simulations show that the capacity of the user with weaker channel gain improves noticeably. Moreover, in a NOMA system with more than 2 users a fixed power coefficient is allocated to the user with the weakest channel condition, and power allocation to the other users is done in a way that the transmitter power consumption is optimized. Computer simulations is carried out to verify the effectiveness of the suggested methods.

Wind turbine-generators shaft is relatively soft and wind turbine mechanical systems is usually represented as two mass model. Two mass model contains torsional oscillatory modes that may be excited under wind speed variations and grid fault conditions. In this state, torsional oscillations may appear on the output responses of the wind turbine-generator. PMSG based WTs include two converters: machine side converter (MSC) and grid side converter (GSC). The main function of the GSC is the dc-link voltage regulation. Also, the MSC is used to control the generator speed or active power, and thus the control of the generator is mainly carried out by the MSC. There are different strategies for the control of MSC. The purpose of this paper is to study different control strategies of the MSC in the PMSG based WTs. These control strategies include turbine-generator control in speed control mode, power control mode or optimum tip speed ratio mode. Then, performance of the WT by using the mentioned control strategies against wind speed changes, aerodynamic power fluctuations due to tower shadow effect and grid voltage dip is examined and compared. Next, by modifying the MSC control, the wind turbine response is improved.

Now days, sharing data in communication systems and computers require high levels of Information security. Side channel attack is one of the methods which it is applied to attack cryptographic systems such as smart cards. In this paper, a new approach for countermeasuring cryptographic algorithms has been proposed and implemented on FPGA. The scheme is based on using Phase Locked Loop in AES algorithm which by disturbing power consumption pattern and execution time of different rounds, the resistance of the algorithm against power attack has been increased. Masking and hiding technique has been used to protect the encryption key. Overall, the proposed method has been simulated within TSMC 65nm technology platform and outstanding success has been obtained; in applying the technique to AES, the overhead was 13% in CMOS area, 15% in power consumption, 2% decrease in working frequency while finding the key became difficult for attackers. In addition, the proposed method has been implemented on FPGA and satisfactory results have been obtained for an acceptable number of samples of the power trace.

In this paper, a new multi-mode control method is proposed to optimize the efficiency of the half bridge converter under the load variations. Efficiency optimization is performed by only changing the control mode and without adding elements to the main converter structure. The control method uses the prominent control modes including asymmetrical, duty phase shift, pulse width modulation (PWM) and burst control. For the first time, three transition points between control modes, being the specific values of the load current, are analytically calculated based on full bridge converter power losses. Transition points are used as the criteria for allocating the control mode and are functions of the half-bridge converter parameters. The proposed method continuously compares the load current with the transition points and puts the converter in the control mode with the highest efficiency. Thus, the half-bridge converter efficiency is optimized in terms of control modes and over the load variations. The accuracy of the analytically determined transition points and superiority of the proposed control method to the previous ones is determined by illustrating the performance of the converter.

Through the passage of time, computer technology has been considered as a pivotal element in human life. Because of this point, it is more evident that information security gained a prominent position. Cryptography is utilized to secure information in a way that information became impenetrable under attack. In this paper, a new method of encryption is introduced according to the theoretical channel coding method and modular calculations. In this method, with the help of science of numerical theory and modular calculations, a method is used to generate dynamic permutation boxes and dynamic subsituation boxes. Then, with the help of information theory and coding, random errors are added to the text. Generated random errors should be detected and corrected at decryption time using decoding methods. The production of an independent cryptographic method with the pattern of intentional error use, along with the use of a shortcut key (256 bits), has the advantage of this method over the pattern-matching methods. This method can perform an encryption algorithm in which the performance of algorithm for a fixed text and a fixed encryption key, produce a differentiated encrypted text, with Hamming distance nearly 50%, in comparison to the previous performances.

The most important issue with trajectory analysis is calculating similarity between trajectories. In this paper a novel method for measuring similarity between trajectories based on the cost to match a set of trajectories segments was introduced. The similarity between two trajectories is defined as a minimum cost to match a trajectory to the other one. For this purpose, the segment based distance was introduced to as a cost of matching two trajectories segments. In addition, the dynamic programming technique is used to implement the time warp method. We performed some experiments to compare the proposed similarity measure with the similar approaches in the application of trajectory classification. The empirical quality of the proposed similarity measure was evaluated on 1-nearest neighbor (1-NN) classification task using 13 publicly available data sets. Compared to the other well-known similarity measures, the proposed method proved to be effective in the considered experiments based on the accuracy of classification.

Data comparison is a fundamental problem in machine learning research. Since, metric learning has various applications in clustering and classification problems, it is attracted much attention in the last decades. In this paper, an appropriate metric learning method is presented to utilize in machine vision problems. Common features in machine vision are often histogram; however, metric learning methods are usually designed based on Mahalanobis distance which is not applicable in histogram features. In this study, a new metric learning method based on modified chi-squared distance (χ 2) for histogram data is presented. In histogram data classification, χ 2 distance is more accurate than Euclidean one; however, its computational cost is higher than Euclidean distance. In this paper, a χ 2 distance approximated formulation where a part of its computations is moved into the feature extraction step in offline phase is proposed. Consequently, computational cost of feature comparison is reduced. Experiments on different datasets show that the proposed metric learning method is more accurate than the existing ones in histogram data classification. Moreover, the approximated χ 2 distance increases feature comparison speed about 2. 5 times without loss of accuracy.

Power plants have noticeable share from underground water consumption. In order to make some water savings, different approaches such as replacing wet cooling towers and installing renewable energy sources have been proposed. These medium and long term approaches however need huge investments and may degrade performance of the system. This paper discusses generation system water consumption minimization as a short term solution. To do so, conventional economic dispatch problem is extended to a multi-objective problem where a linear combination of electricity generation cost and water consumption is minimized. The paper presents estimation procedure of water saving cost function in a generation system. Then, a test system is applied to determine potentials and costs of saving water in a generation system. Different studies are conducted and the results are presented. Finally, water saving cost function is estimated for the generation system. According to the results, some relevant conclusions are drawn.

Wireless sensor network (WSN) consists of some small and cheap nodes which could communicate together, process gathered data, and sense the environment. Today’ s developments in wireless communication systems, causes higher data rate for multimedia applications. The optical wireless communication (OWC) can provide higher data rates and more secured communication links rather that radio frequency (RF) technology for some applications such as underwater communications. In this paper, the optical technology is employed for data transmission in WSNs. An optical wireless sensor network (OWSN) is realized based on sensor nodes and cluster head (CH). Different hardware parts of designed sensor boards are evaluated and the optical communication parameters are measured. An optimized media access control protocol called VMAC is presented. In the proposed OWSN, both nodes and CH are modular. The experimental results show that the maximum transmission distance for 300bps and 600bps baud rates are 18m with 0% BER and 21m with 10% BER, respectively.

Vector Quantization (VQ) is the powerful technique in image compression. Generating a good codebook is an important part of VQ. There are various algorithms in order to generate an optimal codebook. Recently, Swarm Intelligence (SI) algorithms were adapted to obtain the near-global optimal codebook of VQ. In this paper, we proposed a new method based on a modified firefly algorithm (MFA) to construct the codebook of VQ. The proposed method merged genetic crossover operator with FA to develop the VQ. This method is called MFA model. Experimental results indicate that the reconstructed images generated by the proposed model is get higher quality than FA and it’ s about one percent, but it is no significant superiority to the PSO algorithm. Furthermore, MFA is slower than FA.

Autonomous hovering of AR. Drone 2. 0 quadcopter, which is an important subject and prerequisite for other autonomous UAV applications, is the goal of this paper. We propose a new method, called GSPnP, for pose estimation using only the bottom camera of the robot. Moreover, an optimal fuzzy controller, called TGM, is designed in order to stabilize the quadcopter hovering. Then, the optimal parameter values for the controller are obtained. The current position of the robot, relative to the ArUco library marker, is computed using our proposed GSPnP algorithm and the images of the bottom camera. The current position is sent to the controller and the output is computed based on the ROS AR. Drone 2. 0 driver and is sent to the robot simulated in the Gazebo world. The results indicate a more accurate and desirable performance of GSPnP method and TGM fuzzy controller in controlling the robot position compared with other methods with an error of less than 30, 40, and 20 millimeters in x, y, and z directions, respectively.

In this paper, a dynamic sliding mode controller with fractional order sliding surface based on backstepping algorithm is designed and presented for controlling performance of a micro-electro-mechanical triaxial gyroscope. To compensate uncertainties and incoming disturbances to the system, a sliding mode controller is used. In order to increase the degree of freedom and further robustness of the controller, the sliding surface is selected as fractional order form. Using dynamic sliding mode controller in addition to the increasing the performance of controller, cause to reduce the chattering phenomenon in the input control signal. Using the backstepping approach as a very powerful design tool for nonlinear systems, makes the designed controller more robust against incoming disturbances to the system. Asymptotic stability of the closed loop system will be proven by Lyapunov stability theorem. At the end of the design, in order to efficacious reduce the chattering phenomenon in the control signal, fuzzy control theory for control the boundary layer and also adaptive method for online estimating the upper bound of uncertainty are used. In order to evaluate performance of the designed controller, this controller is compared with two other sliding mode controllers. Simulation results show that the proposed controller have a much less chattering phenomenon in control signal, increasing system stability, reducing the rise time and better tracking.

The design of a compact wideband polarization splitter based on Mach-Zehnder interferometer (MZI) with non-uniform multi-mode interferometer (MMI) couplers is presented in this manuscript. The polarization splitting in the proposed structure stems from polarization dependent dispersion of non-uniform silicon-on-insulator (SOI) waveguides used as the MZI arms. The use of non-uniform MMI couplers increases the bandwidth of the structure while reduces its sensitivity to fabrication imperfections. Our simulation results show the very low insertion loss of 0. 8dB, and high polarization extinction ratios of 10dB and 15dB for transverse magnetic and transverse electric field polarization, respectively, in the ultra-wide bandwidth of 100nm (1500nm-1600nm). The proposed polarization splitter has wider bandwidth and larger fabrication tolerance compared to the directional coupler based splitter. In addition total footprint is 3. 86×60 m2 which is much smaller than MZI based splitters.

Vessel traveling at sea causes hydrodynamic anomalies in sea water called Kelvin waves. Motion of conductive sea water due to Kelvin waves in natural Earth's magnetic field makes these waves visible using magnetic transducers. Geomagnetic anomaly induced by the motion of vessels may extend several kilometers and stay up long hours under certain conditions which consider this geomagnetic anomaly as a good candidate in marine surveillance. From remote sensing point of view in this work, we proposed a method for detecting vessel geomagnetic anomaly using an airborne magnetic sensor. Analytical formulations are derived and shown that physical properties of hydrodynamic Kelvin waves in shallow water are directly related to vessel parameters such as speed and traveling direction. Numerical simulations are used to demonstrate the applicability of our results. Vessel detection is performed in frequency domain. It is shown that the proposed detection method is noise robust and can be used to detect a vessel in a noisy ambient. Effect of vessel parameters such as velocity and traveling direction in frequency spectrum of received signal are investigated.

A suitable energy management system (EMS) is an essential tool for optimal operation of a Microgrid with different resources considering uncertainties. In this paper, a day-ahead stochastic EMS is proposed in order to minimize the cost operation and maximize the reliability of Microgrid. The proposed EMS should supply electrical and thermal loads of Microgrid. A stochastic framework based on scenario generation is used to response the uncertainties of electrical load, market price and renewable energy sources (RESs). Also demand response programs (DRPs) are provided based on various load shifting contracts to consumers. In addition, both islanding and grid-connected operations of Microgrid are handled. Capability of the proposed method is proved by simulation results of a 3-feeder Microgrid with 7 generation units.

Intrusion in the network is increasing. Intrusion detection system can greatly prevent network attacks. Feature selection is a critical issue in intrusion detection systems which have a considerable impact on the accuracy and effectiveness of the system. In this study, a new hybrid network intrusion detection system with improved artificial bee colony algorithm using support vector machine classifier is proposed for feature selection. The main idea is utilizing a combination of search equations of particle swarm optimization and Differential Evolution for updating bee’ s position of employed and onlooker bees and utilizing levy flight on scout bees phase, to improve exploitation and increase the convergence rate of the standard artificial bee colony algorithm. The robustness and stability of the proposed approach is evaluated on NSL-KDD dataset and showed significant improvement on the overall performance of intrusion detection system with an accuracy of 98. 97 percent.

In this paper, the simulation, analysis and design of a filtering antenna (filtenna) has been presented. A rectangular microstrip antenna and a parallel-coupled half-wavelength resonator filter are combined together to design a filtenna. This structure has a substrate with dielectric constant of 2. 6. The proposed structure form a forth order band-pass filter with Chebyshev response and center frequency of 2. 45 GHz. First, a parallel-coupled half-wavelength resonator filter was designed using Filter Synthesis Approach, then a microstrip rectangular patch was used instead of the last resonator of filter to act not only as the last resonator of filter, but also as a radiating element. The 3-dB bandwidth of the structure is 260 MHz and the-10-dB bandwidth is equal to 10. 5 percent. The proposed filtenna has a good out-of-band gain suppression, flat in-band gain, and well-shaped radiation pattern. The performance of the proposed filtenna has been simulated with HFSS.

This paper presents a new method for proper modeling of time domain multi-ports grounding systems that can be implemented in transient state-of-the-art analysis software. The presented method aims in minimizing the approximation in the frequency modeling of grounding systems in the transient analysis of power systems. The proposed solution is divided into three stages: First, the use of an electromagnetic method for solving the Maxwell equations, which leads to the extraction of the impedance matrix of the grounding system in a desired frequency range. In the next step, a logical approximation of the impedance matrix was made using the Vector Fitting (VF) method. The used VF method has led to the fitting of a set of poles for all impedance matrix arrays. In the final stage, considering that all the transient soft wares analyze power systems based on the admittance matrix, the proper model of the time domain multi-ports grounding system is executed by state space equations. The proposed modeling is performed on a typical 132 kV transmission line, and performance of implemented grounding system is compared with the previous methods including admittance matrix modeling and conventional model based on simple linear resistances.

A novel methodology is proposed for offset cancellation in single-stage latched comparators at high comparison speeds. In contrast to the regular methods, high-gain op-amp is not required and the loop accuracy is enhanced by small variations on the body voltages of PMOS devices. Hence, the number of digital signals which are transferred to the analog section are reduced and digital coupling effects are considerably improved. A novel read-out circuit is also proposed which compensates the parasitic capacitance of the next cell and quadruples the fan-out of the comparator, consequently. Worst-Case simulation results confirms that the proposed comparator can detect 1. 5mVolts input difference, at all process corners, in presence of 15mVolts input offset voltage, at 800MS/s comparison rate. The Monte-Carlo analysis for 100 iterations on input offset voltages shows that input referred offset would be improved to 150μ V while was 25mVolts at 3σ before the correction. Power consumption is 0. 55mW at 800MS/s comparison speed. Post-Layout simulation results are presented using the BSIM3v3 model of a 0. 18μ m CMOS technology.

In this paper, we investigate the detection of masked weak moving targets in the adjacent fast strong target by using FAPC algorithm. The matched filter of conventional pulse compression radars induces range sidelobes in surrounding a target with high SNR that could mask the smaller targets. The mismatch created in received signal by Doppler phase shift, degrades APC filter performance in side lobe suppression. In this paper, the FFL-FAPC algorithm is proposed to reduce the range side lobes using the RMMSE estimator in its post-processing method. In various scenarios, we will investigate the detection of masked targets in comparsion with previous methods. Simulation results show that the FFL-FAPC algorithm reduce significantly of computational cost, in addition to provides improved Doppler robustness.

Microprocessor designers use the design of multicore systems on a chip to increase their computing power. Adding the number of cores leads to an increase in the power density, followed by enhancement of temperature. Reactive and proactive approaches are two sets of the methods for managing the temperature. Unlike the reactive methods that act based on threshold temperature, proactive approaches utilize a thermal prediction model in thermal management. In this paper, two multilayer perceptron neural networks has been used for thermal prediction and temperature control. An appropriate dataset is provided for training each model. This dataset consists of some features that are read by sensors and measurement tools and new features that are produced by proposed processes. In this regard, historical features are suggested for thermal model. Proper features of thermal model are selected by using feature selection based on mutual information. The temperature is controlled by setting the processor frequency and fan speed. The features of control model are selected by non-dominated sorting genetic algorithm. The error of thermal model for different time distances is about 0. 5 ° C. The thermal control model has respectively 2% and 0. 6% errors in determining the processor frequency and fan speed.

The growing demand for high-quality services together with the rapid increase in number of users have made the high data rate as one of the basic requirements of the next generation broadband wireless networks. One of the proposed solutions for this purpose is the Orthogonal Frequency Division Multiplexing (OFDM), which is used in various standards, such as IEEE 802. 11. On the other hand, OFDM System’ s performance is highly affected by carrier frequency offset and time offset. Therefore, one of the essential requirements of each OFDM receiver is its capability in performing accurate time and frequency synchronization. Hence, in this paper, a joint time and frequency synchronization method for communication systems based on IEEE 802. 11 is proposed. As the IEEE 802. 11 standard uses training sequence or preamble in its frame, synchronization methods employed in this standard should be based on using such training sequences. Then, based on different metrics and using computer simulations, the performance behavior of the proposed method in AWGN and multipath fading channels is evaluated and compared with various training-based synchronization methods. Simulation results verify desirable performance of the proposed method in practical scenarios.

In this paper, a novel structure of diplexer is designed based on Substrate Integrated Wave guide (SIW) technology and S-shaped complementary split ring resonator to operate in LTE1. 3 GHz-2. 1 GHz band. A miniaturized and compact SIW diplexer implemented by Crisped S-shaped Complementary Split Ring operated in a waveguide format is proposed and presented. In design process, firstly, the filters corresponding to each of the bands is designed in simulator, then by using S-parameter of each filter the T-shaped structure dimensions of the input feeding diplexer is achieved and optimized. It is deduced from measurement results of diplexer that input and output impedance matching in the respective bands, transmission losses are1dB and 2dB for 1. 3 GHz and 2. 1 GHz respectively. The isolation between output ports is better than 30dB. Finally the proposed structure reflects the performance is highly desirable. This structure illustrates advantages in terms of the small size, low loss, high isolation, easy realization and integration with other planar circuits.

Since validation of the electromagnetic parameters of manufactured or purchesed ferrite materials is the first step in designing and implementation of the diffrent ferrite-based devices in communication systems, ferrite characterization is verry important. in this paper an algorithm is simulated and implemented which is based on the minimization of an objective function. the objective function's parameters are the reflection and transmission coefficients of the ferrite in a rectangular wave guide. in compairsion with other works proposed method only needs to the amplitude of the reflection and transmission coefficients to estimate the parameters of ferrite materials. This makes the implementation easy and eliminates the problems associated with phase calibration and sensitivity. The proposed method is simulated for a nickel ferrite and experimentally tested on SL-470 ferrite sample and the results have been compared with the manufacturer's catalog.

In this paper, a band-pass filter with suitable performance for wireless telecommunication applications is designed and fabricated. For designing the proposed filter, the dimensions of dual-mode square patch resonator are chosen to be within a quarter of the wavelength. Circular perturbations (circular slots) are used for better performance of the proposed filter. A dual channel filter is designed and fabricated on an FR4 substrate. The center frequency of the proposed filter for the first channel is equal to 2. 35 GHz and for the second channel is equal to 3. 375 GHz; the 3-dB fractional bandwidths (FBWs) of 12. 75 and 10. 3 %, respectively. The measured insertion losses are 0. 8 and 1. 45 dB, respectively. The proposed filter has a small size of 20 mm × 20mm. The group delay of the proposed filter for the first and second pass bands is almost constant, which indicates phase of the insertion loss in the pass bands is linear. The proposed filter is fabricated and tested. The results of simulation are fairly consistent with that of the measurement. The proposed filter can be used in wireless communications and modern microwave telecommunication.

One method of design the LFSR-based stream ciphers is using irregular clock that it is most famous structures. In recent years became a springboard technique called clock control that improves efficiency compared to generators has become tighter. In this way, instead of several clock has been changed and values, in the state through the middle. Per basic polynomials, a jump in the index jump is still there. It is clear that for the length of each LFSR, there are several initial polynomials that same period, but the size of the jump index is different. In this paper, by analyzing the correlation attack on generators springboard, it was concluded that the selection of index jump polynomials with maximum results in minimum correlation between output and input sequence is productive. So in the design of stream ciphers with a springboard generation structure, in terms of correlation attacks, the polynomial with most rate of jump up the index is priority.

The ability of network generators to maintain their synchronism after a fault depends on several factors, including the initial conditions of the system before the fault, so it can be expected that by changing the system variables, such as the angle of the generator rotors in the system, the system stability can be against the fault. This change is possible by the Permanent presence of FACTS devices. The critical clearing time of fault as the most accurate criterion for transient stability evaluation can be the objective function of our optimization problem, but the determination of the critical clearing time, which involves the time domain simulation of the network along with the repeated examination of the fault occurrence It is time consuming to adjust the FACTS devices to a power system that is changing at any one time. In this paper, we present a new objective function based on the reduction of the voltage angle difference between generators terminals, which greatly increases the speed of optimization, in order to improve the transient stability of smart grid by setting up the online FACTS devices. Minimizing this objective function by optimizing the FACTS is equivalent to maximizing transient stability. In addition to optimal tuning, optimal type, number and allocation of them are considered for long term. in determining the optimal number of these devices, the cost of investment is also considered.

The low altitude primary search radar use a continuous wave, and in its simplest case, a sawtooth modulation is used in one scan and no modulation in the next one. By determining the frequency of the returning signal in two consecutive scans, the target range and radial velocity are extracted. In this method, the two successive scans are needed to determine the range and this is one of the main problems of this method. In order to simultaneously extract the radial velocity and the range, the modulating waveform is changed to a triangular wave form, and simultaneously two preprocesses are proposed to compensate for the spectral spreading by sampling and smoothing the returning signal. This has a significant effect in determining the exact components of the target in the low signal-to-noise conditions. Also, a simple algorithm is proposed to determine the coupled frequency components of the target in the pre-processed spectrum more accurately. The processing was done by using a TMS320C6416 DSP processor on an actual radar signal. The experimental results show a higher stability and less error in determining the range compared to other methodes.

The performance of a switched capacitor circuit strongly depends on its analog switches. This paper introduces a new technique to design a high precision analog MOS switch for switched-capacitor applications. To satisfy the accuracy requirements of the switch, a novel technique is proposed to minimize the charge injection and clock feed-through errors by using a very simple structure. Moreover, an innovative approach to increase the off-resistance of the switch and consequently minimizing its leakage current is presented. In order to evaluate the performance of the proposed switch, simulations are done in a 18μ m standard CMOS technology. The on-resistance of the proposed switch is less than 560Ω over entire input signal range which completely satisfies the tracking bandwidth requirements. In addition, since the proposed switch provides an ultra-high off-resistance in the range of several GΩ s, the leakage current of the proposed switch is negligible. Simulation results also show that switch induced errors are significantly eliminated by using the proposed cancellation technique. The output error charge due to charge injection and clock feedthrough over a wide range of the input signal variation is less than 1. 6fC. Moreover, simulation results show that the proposed switch achieves signal to noise plus distortion ratio (SNDR) of 80. 55dB, effective number of bits (ENOB) of 13. 08, total harmonic distortion (THD) of-81. 41dB and spurious-free dynamic range (SFDR) of 87. 7dB for a 2. 5MHz sinusoidal input of 800mv peak-topeak amplitude at 200MHz sampling rate with a 1. 8V supply voltage.

In this paper, in order to evaluate new materials for design and simulation of the field effect transistors in nano dimensions, we simulate and investigate the electronic properties of a field effect transistor based of topological insulator. Since the energy gap in the channel region of this transistor is adjustable by a perpendicular magnetic field, first by obtaining the transfer characteristics, we analyze the DC characteristics such as Ion/Ioff ratio and the threshold voltage. Moreover, we evaluate the short channel effects (SCEs) including subthreshold slope (SS) and drain induced barrier lowering (DIBL). The obtained results for (SS) and (DIBL) for m=1 show the values of 8. 24mV/dec and 0. 064, respectively, which are very suitable for transistor applications. Finally we achieve the analog characteristics of the simulated field effect transistor such as transconductance, output conductance, output resistance and voltage gain and study the parameters affecting these figures of merits.

The tremendous growth in the demand for high data-rates in optical networks makes efficient use of available bandwidth indispensable. Network's throughput can be improved by exploiting high-level modulation formats which allow the transmission of high data-rate and upgrading the quality of optical communication signal which degrades due to transmission impairments. The nonlinearity of optical fibers has been long recognized as one of the most overriding factors limiting the quality of optical communication signal. Accurate evaluation of nonlinearity in generalized multiprotocol label switching (GMPLS) optical networks is more complex and costly. In this paper, we present a novel heuristic joint routing, wavelength and power allocation method for path computation element (PCE) based architecture for GMPLS optical networks such that launch power of the lightpaths are updated continuously, thereby the minimum number of lightpaths are assigned to the demands. The Gaussian noise (GN) model is exploited to capture the nonlinear effect and we focus on maximizing the Shannon sum rate for network. In the DTG network compared to existing methods, numerical results demonstrate that the number of higher order modulation formats is increased and the network throughput is improved about 138. 4 THz.