مجله مهندسی برق و الکترونیک ایران
سال بیستم شماره 3 (پاییز 1402)

The present work applies the holographic technique to develop a leaky-wave antenna based on spoof surface plasmon polariton with circular polarization. For the first time, an impedance surface (hologram) with an anisotropic unit cell (with a hollow metallic cross-bars shape) without a ground plane is implemented to control the radiation polarization of the leaky wave structure. We used a combination of optical conversion relations and a particle swarm optimization algorithm to estimate the anisotropy of the proposed unit cell. By changing the dimensions of the cross's two arms and rotation angle, the required components of the surface impedance tensor are determined to realize the hologram. The realized gain, radiation efficiency, sidelobe level, and axial ratio bandwidth are 15.3dBi, 82%, -11dB, and 11.8%, respectively. The maximum scanning angle of was obtained when the frequency varies from f = 16 GHz to f = 18 GHz. The simulations were performed in MATLAB and CST Microwave Studio.

In this paper, the problem of distributed high-dimensional nonlinear target tracking over radar networks is investigated. Since radar performances are different in range and measurement functions, utilizing radar networks, data fusion, and data processing increase the accuracy of tracking. Among all data fusion methods for radar networks, distributed manner gains the most reliability and less computation burden with high tracking accuracy. First, nonlinear radar measurements are processed by a local cubature Kalman filter in each agent. Secondly, all processed data over all agents reach an agreement by utilizing a weighted average consensus filter. The proposed algorithm using the consensus on information method decreases the tracking error and computation burden and guarantees the boundedness for any number of consensus steps. Finally, the efficiency of the proposed algorithm and superiority to traditional methods is demonstrated by performing a numerical simulation of tracking a maneuvering target.

Ultrasonic phased array imaging has found wide applications in industrial non-destructive test (NDT) including defect and crack detection in industrial samples and weld inspection. In this paper, an approximated minimum variance based beamforming method is proposed to improve the defect detection accuracy and reducing the background noise in the phased array ultrasonic imaging. The proposed method is employed in the boiler tube NDT. The matrix inverse approximation is computed using matrix inverse lemma such that the beamforming is performed proportional to the received signal amplitude. The performance of the proposed method is quantitatively and qualitatively evaluated in both theoretical and practical tests and compared with similar beamforming techniques. It is shown that the proposed method is able to reduce the image background noise while keeping the defect detection ability in comparison to both delay-and-sum and adaptive minimum variance beamforming methods. It also leads to defect detection enhancement compared with the minimum variance method. The computational complexity of the proposed method is less than that of both conventional and adaptive minimum variance beamforming methods.

This research proposes an appropriate tone mapping approach to obtain images with low dynamic range or LDR from images with high dynamic range or HDR. The proposed method uses a type of adaptive bilateral filter, where the spatial and range similarity parameters of the filter are determined separately for all pixels through the gradient map. By assigning larger similarity parameters to the pixels of the flat areas compared to the pixels of the non-flat or edge areas, the proposed filter is able to more accurately match the extreme changes of the pixels of the HDR images to reduce the effect of the bright pixels of HDR images on the adjacent dark areas and prevent halos in corresponding LDR images. Also, to prevent the possible distortion of the color components in the tone mapping operation, the V channel of the HSV color space has been used. To speed up the operation, the accelerated example of the proposed adaptive bilateral filter has been used. The results of this research confirm the effectiveness of the proposed algorithm in producing high-quality LDR images as well as the acceptable execution time compared to similar algorithms.

Due to the three undesirable factors of absorption, dispersion and turbulence induced fading, performance of underwater visible light communications (UVLC) is severely reduced. In this paper, performance of a multi-input single-output (MISO) ULVC broadcasting with DC-biased optical filter-bank multi-carrier (DCO-FBMC) modulation using offset-QAM (OQAM) has been studied. The OQAM DCO-FMBC has higher spectrum efficiency than DCO-OFDM modulation since it does not need cyclic prefix; however, due to inherent inter-symbol interference (ISI) and intercarrier interference (ICI), bit-error rate (BER) of OQAM-DCO-FMBC system is saturated in high data rates under adverse conditions of ULVC channel, especially turbulence induced fading. In order to deal with undesirable factors of underwater channel, as well as minimizing the inherent interference of OQAM DCO-FBMC modulation, employing multi-tap precoders in the transmitter is recommended; therefor, performance of a downlink system for transferring data from a MISO base station with space diversity to multiple mobile users in the ULVC channel has been investigated. Computation of precoder coefficients are done by minimizing the mean square error (MMSE) according to the channel state information (CSI). simulation results show that the proposed method can significantly improve the system performance in UVLC channels with weak turbulence as well as reducing absorption and dispersion.

Ordinary differential equations play an important role to describe dynamic behaviors in different engineering systems. On the other hand, high-speed computations and broadband signal processing are achievable using compact photonic integrated circuits with low power consumption. So, in this paper, a dual-purpose compact all-optical integrated circuit consisting microring resonator, directional coupler, splitter, and subtractor has been designed and analyzed for ultra-fast signal processing. This all-optical circuit can be utilized simultaneously as a first-order differential equation solver and a first-order differentiator. Full-wave analysis for the mentioned components of this integrated circuit has been performed by frequency-domain simulations, and their performance has been investigated carefully. Also, performance of the designed circuit has been analyzed using the numerical three-dimensional finite-difference time-domain (3D-FDTD) method considering a Gaussian input pulse. This circuit has unique features such as high-speed performance, compactness, and compatibility with the CMOS technology.

In quantum secure dialogue, or bidirectional quantum secure direct communication, the users exchange information simultaneously and bidirectionally. In this paper, a secure quantum dialogue which is immune to collective noise has been proposed. In this schema, the data of two users is divided into three-bit sets and is transmitted using two GHZ states simultaneously. This scheme uses the entanglement swapping to produce the initial state. In this method, the eavesdropper attacks are disclosed and it has no information loss. The performance of this protocol has increased compared to previous protocols. The best efficiency of the previous protocols was 25%, but the proposed protocol reached 42.85%

A practical low-complexity implementable coding scheme is considered for a two-link binary Chief Executive Officer (CEO) problem in this paper. The proposed scheme is based on the binary quantization and the Slepian-Wolf (SW) coding problem. It is shown that the source splitting technique is an efficient method for achieving non-corner points of the achievable rate region of the SW problem. Decoding is accomplished by employing iterative message passing algorithms for the Wyner-Ziv (WZ) problem, in the proposed scheme. We show in this paper that applying iterative message-passing schemes yields a close rate-distortion performance to the Berger-Tung inner bound of the binary CEO problem.

In this paper, a perfect metamaterial electromagnetic absorber with a simple design is presented at microwave and terahertz frequencies. The designed absorber includes a metamaterial layer including thick cross hollow deposited on substrate terminated by a metallic back reflector. The perfect absorption can be achieved with proper design of the dimensions of the structure at the microwave and terahertz frequencies. As an application, the proposed absorber can be used as a sensor to detect different refractive indices. The results show that the proposed refractive index sensor can be utilized to detect the level of glucose in water with a sensitivity of 10.83 Gigahertz per refractive unit (GHz/RIU) and Figure of Merit (FOM) of 43.4 (1/RIU). However, the proposed structure can be used to diagnose other biomedical features as well.

Distributed estimation in communication networks is an issue that has received a lot of attention recently. One of the most challenging issues in these networks is the communication reduction of the network. Recently, researchers have proposed methods to reduce the communication load that while reducing the communication load in the network, have less impact on the final performance of the network. For signal processing in nonlinear space, correntropy has been regarded as an information criterion in recent years. Of course, in Gaussian space, the use of correntropy does not always work well, but if we have impulse noise, the cost function based on correntropy is better than the cost function based on square estimation error. In this research work, network noise is impulse noise. To have less destructive effect on the final performance of the network, a new solution is presented based on information criteria. Correntropy is a good criterion as a measure of similarity between two random variables that are in the same space and also because correntropy is not sensitive to sudden changes. Node deletion is performed intelligently and based on correntropy between the reference node and neighboring nodes. Also, a mathematical analysis shows that the condition of deletion of nodes is not dependent on the parameters of the correntropy kernel. The simulation results show that this method has less final MSD than other methods of reducing the network communication load.

Luby Transform (LT) codes are the first realization of a class of fading codes, which we call pervasive fading codes. The properties of such codes are well defined when using large data files, but they do not perform well when used for short messages. In this paper, a new encoder and decoder, specifically an efficient LT encoder using the Robust Soliton Distribution (RSD) as a new right-degree distribution and a new left-hand distribution tested in the Binary Erasure Channel (BEC) is introduced. The left-degree distribution of an LT code is intended as a Poisson distribution for general protection. Left-degree shaping creates better performance than LT code, which is compared to high-performance designs in other papers. In information blocks with length k = 256 and bit error rate 10-8, the realized coding rate of this model is 0.58, which is 25% more than the developed BP design of Mr. Jamshidi and his colleagues. Experimental results show that this new codec leads to improvements in all system features. As such, it is a step towards designing and building better code for the BEC channel.

Nowadays is era of Internet of Things. Load balancing is an important studying issues in internet of things that intended to improving energy consuming with distributing loads. The IoT needs load distribution because of the use of Wireless Sensor Networks (WSN) as one of the most well-known IoT connection participators. Improved routing in network is one of methods of load distributing and balancing energy consuming. Software Defined Network (SDN) is a new network architecture with could reach this goal, using central controller. In this paper balanced routing based on Leach is presented, which is one of important routings in wireless network. Proposed algorithm is done using direct monitoring of information of load of link and the running situation. This routing named SDN-Improved LEACH which can send different flows to BS with the best route. In this routing, using the proposed new controller architecture and defining different layers and units for it, optimal routing for current transmission is considered. This routing directs packets from one source to another according to network conditions. At the end, proposed routing is compared with leach and improved leach algorithms which are some of important routings considering different parameters. Comparisons is done in the number of live nodes, mean consumed energy, receiving data and number of lost packets. comparing diagrams are drowning at the end of paper that indicates predominance of proposed algorithm in compare of those two algorithms.

Pattern mining on paths and roads data has brought up valuable and effective achievements in different areas, such as: roads and urbanization, transportation, and even forecasting social services. The trajectory patterns of moving objects in road networks were examined to extract efficient patterns. Among the challenges in clustering techniques of pattern mining is to find consecutive patterns with low run time. To solve this problem, a clustering algorithm was proposed titled BFEs-Enhanced, which can be used to extract sequential and meaningful flock patterns with a short time interval. Simulation results showed that the proposed method, thanks to the use of efficient criteria for clustering, such as maximum distance and minimum number demonstrated an outstanding performance. In addition, a new criterion was added to the algorithm called minimum time period. Along with the distance criterion in BFE-Enhanced algorithm, the criterion of direction was also added to the algorithm to improve its accuracy. Therefore, the proposed algorithm is featured with a shorter time interval and higher number of meaningful and sequential patterns.

With the rapid spread of technology, large volumes of unlabeled data with large dimensions needed to be processed. To reduce the dimensions, unsupervised feature selection is known as an important pre-step before machine learning tasks. In this paper, an unsupervised feature selection method is proposed. The method works dynamically and is scalable based on matrix graphs and weighted matrices. To improve the performance of this method, instead of using the Lagrange function to construct a weight matrix, a bipartite graph theory is applied. Feature selection is done on the matrix graph. This graph is constructed using k nearest neighbors, which makes the method more robust to noise. The global structure of the original data is also preserved by constructing a Reconstruction Weight Matrix with low-rank constraint. In addition, the feature score, which explicitly reflects the strength of the features, is modeled using the Frobenius norm function. The proposed method is compared with similar methods in three criteria of classification accuracy, parameter sensitivity and complexity. Experiments show that the classification accuracy of the method presented in this paper has improved by an average of 2.83%. Its complexity has also been reduced to max{O(n2d),O(nm)}, where n is the number of samples, d is the number of features and m is the number of anchor points.

In this paper, information of gyroscope and star tracker attitude sensors are fused for attitude estimation in the presence multi-rate sensors and the star tracker measurement delay. To this end, the extended Kalman filter (EKF) is modified to reduce the computation burden avoiding computation repetitions after arrival of the delayed multi-rate measurements. The algorithm is modified such that it is truly estimating the attitude in the absence of the star tracker measurements due to low sampling rate frequency and the estimation is optimized after its arrival. Toward this, the idea of predicting the measurement model, firstly proposed in [7], is employed and extended for the EKD based attitude estimation in the presence of multi-rate gyroscope and star tracker sensory information and delay in the star tracker measurement is also involved in the proposed method. The efficiency of the proposed method is finally demonstrated through both simulation and experimental data.

In this paper, an optimal robust nonlinear control approach based on the state-dependent Riccati equation (SDRE) is presented for a class of fractional-order nonlinear systems. The SDRE control is a method for the solution of nonlinear systems optimal problems, which has some disadvantages, such as it is not robust against disturbances and uncertainties and has not finite time convergence ability. Sliding mode control (SMC) is also a common method for nonlinear systems control, although it is not an optimal control method, it has great advantages such as robustness which has made it very popular. In the proposed method, a combination of SMC and SDRE methods is used for optimal and robust nonlinear control, which is suitable for a class of fractional-order nonlinear systems. The proposed control method has a robust structure against mismatched disturbances. The closed loop system stability is guaranteed by the Lyapunov theory and simulation examples show the performance improvement of the proposed method.