TABRIZ JOURNAL OF ELECTRICAL ENGINEERING
Year:2023 | Volume:53 | Issue:1|Papers Count:7

Microwave photonic oscillator based on optical resonator is one of the leading technologies in the field of microwave signal generation with low phase noise. There are several advantages of using an integrated optical resonator as an energy storage optical element in a microwave photonic oscillator instead of a long optical fiber, such as it significantly reduces dimentions of the oscillator, reduces sensitivity to environmental conditions, etc.. In this paper, two integrated Bragg grating optical resonator are designed and simulated and their applications in an integrated microwave photonic oscillator is investigated. Two types of integrated optical resonator are designed and simulated; I) phase shifted Bragg grating, and II) Moiré Bragg grating. Both resonators have resonance at 1549 nm. The simulated resonators are used in a microwave photonic oscillator and oscillate at a frequency of 20 GHz. Phase noise of the oscillators is calculated based on the Leeson model. By using these integrated optical resonators a phase noise of about -93 dBc/Hz at 10 kHz offset frequency from 20 GHz oscillation is achieved.

A novel bias regulator circuitry is introduced for the class-C LC-VCO in this paper, that results in reduced phase noise and amplitude-enhanced and more robustness of start-up than conventional class-C VCO. Setting the bias voltage is such that in the start-up, Vbias to be larger than the threshold voltage and provide a safe start-up, then in the steady state oscillation, it goes less than Vth and increases the maximum oscillation amplitude. In the proposed bias circuitry, by combining the ring oscillator circuit and a rectifier and two inverters in the first stage, a step voltage signal is created which changes from 0 to VDD and then by applying it to the second stage and the switching operation of the transistors in this stage, the appropriate Vbias is provided. The proposed VCO is implemented in RF 0.18um CMOS process and is simulated by Cadence. Based on the post layout simulations results, the phase noise of the proposed VCO is -121.3dBc/Hz at 1MHz offset frequency from a 5GHz carrier and the power consumption is 2mW, resulting in a FoM of 192.24dBc/Hz.

Approximate computing has emerged as a new method to overcome the delay, energy consumption and area consumption of digital circuits. In this paper, a new approximate full-adder cell, which is based on the combination of the standard CMOS and pass transistor logic styles, is presented. The critical path in the structure of a ripple adder equals only one transistor; Therefore, the adder circuit has high speed. Carbon nanotube field-effect transistor (CNFET) technology is used to simulate and implement the proposed cell. Comprehensive simulations are carried out using HSPICE tool against different power supply voltages, output loads, and ambient temperatures. Simulation results confirm that the proposed cell is more efficient than its counterparts in terms of delay, power-delay product (PDP) and energy-delay product (EDP). At the application level, using the MATLAB tool, the application of image blending is used to evaluate the efficiency of the proposed cell. Simulation results of image processing confirm that the proposed cell has a reasonable performance and produces output images with suitable quality for human inference.

One of the most widely used beamforming algorithms for the application of speech enhancement is the Minimum Variance Distortionless Response (MVDR) technique. The optimal coefficients of the MVDR beamformer are calculated based on the incoherence assumption of environmental interferences and the desired signal. Due to the nature of noise and speech signals, this assumption is not valid in many practical situations. This, in turn, results in inaccurateness of derived coefficients of the MVDR. In this paper, as the first change in the MVDR beamformer, by applying the eigenvalue analysis to the desired signal covariance matrix and removing small eigenvalues, the accuracy of the beamformer coefficients is improved. As the second contribution, we use a generalized version of the Short-Time Fourier Transform (STFT), namely the Short-Time Fractional Fourier Transform (STFrFT), to calculate the MVDR beamformer weights. In this research, after obtaining the optimal value of STFrFT parameter experimentally, the effect of each of the above two changes on the performance is investigated and compared with the basic methods. The results show that the proposed methods, while being stable to the changes of parameters and environmental conditions, achieve signal-to-noise ratio (SNR) values between  and , while the performance of the baseline method is in the range of . Although each of the above changes alone improves the performance, it is noted that the superior performance is obtained when both changes are applied together on the beamformer.

Security of communications is a foundation for interactions in the cyber space.  Recent advances in the field of quantum computing has attracted attentions to quantum attacks. Post-quantum cryptography is a relatively new field of research and few post-quantum protocols have been proposed for secure communications. In particular, authentication of the two communicating peers while preserving their privacy and anonymity is a real challenge. In this paper, we propose a comprehensive protocol for secure authentication, key agreement, and message encryption which is resistant to quantum attacks. We use the blockchain technology and a smart contract for authentication, and the double-ratchet protocol for end-to-end encryption. Our initial key agreement uses post-quantum cryptography which brings a high level of security to our protocol. We store public keys on a cloud storage for saving costs but authenticate them using smart contracts. Our analysis of the proposed protocol demonstrates our superiority from privacy, security, and performance aspects in comparison to the related works.Security of communications is a foundation for interactions in the cyber space.  Recent advances in the field of quantum computing has attracted attentions to quantum attacks. Post-quantum cryptography is a relatively new field of research and few post-quantum protocols have been proposed for secure communications. In particular, authentication of the two communicating peers while preserving their privacy and anonymity is a real challenge. In this paper, we propose a comprehensive protocol for secure authentication, key agreement, and message encryption which is resistant to quantum attacks. We use the blockchain technology and a smart contract for authentication, and the double-ratchet protocol for end-to-end encryption. Our initial key agreement uses post-quantum cryptography which brings a high level of security to our protocol. We store public keys on a cloud storage for saving costs but authenticate them using smart contracts. Our analysis of the proposed protocol demonstrates our superiority from privacy, security, and performance aspects in comparison to the related works.

Face recognition from digital images is used for surveillance and authentication in cities, organizations, and personal devices. Internet of Things (IoT)-powered face recognition systems use multiple sensors and one or more servers to process data. All sensor data from initial methods was sent to the central server for processing, raising concerns about sensitive data disclosure. The main concern was that all data from all sectors that could contain confidential information was placed in a central server. Federated learning can solve this problem by using several local model training servers for each region and a central aggregation server to form a global model in IoT networks. This article presents a novel approach to optimize data transfer and convergence time in federated learning for a face recognition task using Non-dominated Sorting Genetic Algorithm II (NSGA II). The aim of the study is to balance the trade-off between training time and model accuracy in a federated learning environment. The results demonstrate the effectiveness of the proposed approach in reducing data transfer and convergence time, leading to improved performance in face recognition accuracy. This research provides insights for researchers and practitioners to enhance the efficiency of federated learning in real-world applications.

In this paper, a novel risk-based, two-objective (technical and economical) optimal reactive power dispatch method in a wind-integrated power system is proposed which is more consistent with operational criteria.  The technical objective includes the minimization of the new voltage instability risk index. The economical objective includes cost minimization of reactive power generation and active power loss. The proposed voltage instability risk employs a hybrid possibilistic (Delphi-Fuzzy)-probabilistic approach that takes into consideration the operator’s experience, the wind speed and demand forecast uncertainties when quantifying the risk index. The decision variables are the reactive power resources of the system. To solve the problem, the modified multi-objective particle swarm optimization algorithm with sine and cosine acceleration coefficients is utilized. The method is implemented on the modified IEEE 30-bus system. The proposed method is compared with those in the previously published literature, and the results confirm that the proposed risk index is better at estimating the voltage instability risk of the system, especially in cases with severe impact and low probability. In addition, according to the simulation results compared to typical security-based planning, the proposed risk-based planning may increase the security and economy of the system due to better utilization of system resources.