نشریه مهندسی برق
سال پنجاه و یکم شماره 1 (پیاپی 95، Spring 2021)

Software Defined Network (SDN) can integrate a lot of network functions such as network resource management into a consolidated framework. TCP operates in these networks with low information traffic characteristics. As a result, it has to continuously change its congestion window size in order to handle drastic changes in the network or its traffic conditions. As a result, TCP frequently overshoots or undershoots its transmission rate, making it a native congestion control protocol. To overcome that problem, we have proposed a new QoS framework for SDN called QDFSN (QoS-enabled Dynamic and Programmable Framework for SDN) which can be effectively applied in Data Centers as well. In this, and by means of AQM (Active Queue Management), a new function for detecting the upcoming congestion situation is designed. In each node, a developed mathematical model is used to calculate the best parameters of the node adaptively, especially the service rate, to minimize the congestion in the network. This model is tested in many NS-2 scenarios, and the results are presented. The results show improvements in selected QoS parameters like throughput and delay. We conclude that QDFSN-based congestion control shortens the process of adapting TCP to network circumstances, and enhances the TCP performance.

An area-efficient wideband receiver front-end for multi-standard receivers is presented. To handle large input signal levels, dual gain modes are employed in the LNA stage. For input signals lower than -17.5 dBm, a noise-canceling balun CG-CS LNA is employed. The LNA features a local feedback loop to reduce power consumption. For input signals in the range of from -17.5 to -5.2 dBm, the CG-CS LNA is bypassed with a balun unit-gain inverter stage. The proposed front-end shows better than -12 dB input matching for both gain modes in the frequency range of 0.4-3.4 GHz. Due to the lack of off-chip balun, the proposed front-end consumes low area. Moreover, the full differential structure leads to enhanced linearity performance. The post-layout simulation results in RF CMOS 0.18 µm process shows the conversion gain of 24.5/13.06 dB in HG/LG modes. The minimum DSB NF is 3.77/9.84 dB, and the third input intercept point (IIP3) is -7.29/-1.8 dBm. The circuit dissipates 12.93 mW with an active area of 0.073 mm2.

Cognitive Radar is a recently presented research topic, in which most efforts has been done for its conceptual description and the adaptive waveform design feature of these radars, while other aspects of additivity for optimum performance of cognitive radars has been ignored. In this paper, a framework for adaptive time resource management in Cognitive Radars is proposed. The main purpose of this paper is proposing an algorithm for time resource management, with incorporation of adaptive waveform design capability of cognitive radars, to enhance the radar performance for an efficient time resource usage. After developing the equations of radar time resource management using adaptive waveform design, an implementable algorithm is proposed for this purpose and its performance is simulated and analysed. The results show that the proposed algorithm resulted in more efficient time resource management compared to the existing ones.

We present the development of a system for the detection and energy spectrometry of alpha particle radiation based on the Commercial Off The Shelf (COTS) CMOS image sensor. The data is read, processed and displayed in real-time using a single-board-computer (SBC). We show that by using image processing techniques, a slightly modified webcam can be used to measure α radiation. In contrast to dedicated measurement devices such as Geiger counters, our framework can classify the type of radiation and can differentiate between various kinds of ionizing radiation. The system was tested with standard Ra and Am alpha sources.

The presence or absence of distributed generation (DG) sources in a distribution network has a probabilistic nature. In the event of connection or disconnection of these sources, the fault current through a relay and the relay operating time are affected, which leads to miscoordination. For solving this issue, coordination constraints corresponding to the presence or absence of DGs have to be considered in the overcurrent relay coordination problem (CP). The incorporation of these constraints increases the operating time (OT) of the conventional overcurrent relays (OCRs). In this paper, a novel adaptive characteristic is proposed to solve this unwanted effect. Accordingly, a function proportional to the equivalent impedance (EI) seen by the relay is added to the relay characteristic. This EI is calculated via in-situ measurement of voltage and current before the occurrence of a fault, continuously; when the fault occurs, the calculated impedance is used in the relay characteristic to determine the OT. The addition of this function to the conventional overcurrent relay characteristic, reduces the effects of disconnecting the DGs on the coordination constraint, and in general, improves the OT of the relay. Based on the analytical relations and simulation results, it is shown that the OTs of the primary and backup relays with the proposed characteristic are improved compared to the relays with the conventional characteristic.

An integrated CMOS, low-power optical communication receiver front-end is designed and presented in this paper for specified applications of 10Gbp/s. The transimpedance amplifier (TIA) stage and the limiting amplifier (LA) stage possess an active feedforward network based on current-mirror topologies and differential topologies, respectively. In order to obtain broadband performance, low-power consumption characteristic and low-occupied area on chip, an active type of inductors are employed in the TIA as well as the LA stage. The performance of the optical system is simulated using 90 Nano-meter CMOS technology parameters, which exhibits power dissipation of only 1.5mW, -3dB frequency of 6.92GHz, 24pA/√Hz input referred noise, and transimpedance gain of 40.1dB ohm for the TIA stage, while, the whole optical receiver front-end consumes 7.7m Watt, providing 71.4dB ohm gain beside acquiring 6.55GHz frequency bandwidth. Finally, the performance of the presented optical receiver front-end as a low-power, 10Gbps block-diagram is justified.

To achieve a low reference spur for an Integer-N frequency synthesizer, a new spur reducing technique was proposed. To reduce the size of periodic ripples on the VCO control voltage, the low pass filter, and the charge pump were added with a spur reduction system.  By lowering the amplitude of the periodic ripple on the VCO control voltage, we managed to lower the reference spur. The introduced technique removes the necessity to decrease bandwidth and CVO gain reference spur suppressing. To demonstrate the effectiveness of the proposed structure, a 2.06 – 2.22 GHz frequency synthesizer was used and the 180-nm CMOS technology was used for post-layout simulation. The proposed frequency synthesizer represents the reference spur of -85.84 dBc at 20 MHz offset and phase noise of -108dBc/Hz at 200 kHz offset frequency also it is locked after 2.8us while occupied 0.35 mm2 of the chip area.

The use of distributed generation resources (grid-connected or islanded) such as solar systems and wind turbines in the form of microgrids can solve problems related to traditional power systems. On the other hand, the monitoring of power quality disturbances in microgrids is an important issue for compensating these problems. Among the various types of power quality disturbances, harmonic distortions are important. Accordingly, in this paper, a computational method has been used based on the recursive least squares withthe variable forgetting factor (VFF-RLS). The prominent features of the proposed method are its high accuracy and speed, as well as identification with a low rate of signal samples. The main aim of the proposed method is to identify the contribution and extent of harmonics and unbalanced in a microgrid equipped with Advanced Metering Infrastructure (AMI). In the proposed method, the identification is based on real-time estimation and using measured data with high computational speed and accuracy. The results of simulation by MATLAB software, and as well as the experimental results using the TMS320F2812 digital signal processor (DSP) show the validity of the proposed method.

In this paper, a new method is provided for Fault-Tolerant Control (FTC) of wind turbine pitch systems. One of the common faults in wind turbines is the defects of the pitch sub-system. Each blade of wind turbines tracks a reference signal; it is generated by the main controller unit, defects of actuators, or disturbance decrease of the reference signal quality. Classic controllers cannot deal with the disturbance and compensate for the faults to maintain system performance in normal operating conditions. For this purpose, a novel method based on Optimal Robust Model Reference Adaptive Control (ORMRAC) is presented, the output of the proposed method is a new adaptive rule. The ORMRAC method is robust, optimal, and fast at the same time. The proposed structure includes Fault Detection (FD) and FTC units. FD acts based on the generation and evaluation of residuals. The residual generation is based on Artificial Neural Network (ANN) model. When there is disturbance or fault in the pitch system and residual exceeds the certain threshold, the FT unit is activated. The proposed FT method is tested and evaluated using a wind turbine simulator based on practical data. The results indicated the proper performance of the proposed method in comparison with conventional MRAC and some other methods.

Regarding optimization problems, there is a high demand for high-performance algorithms that can process the problem solution-space efficiently and find the best ones quite quickly. An approach to get this target is based on using swarm intelligence algorithms; these algorithms apply a population of simple agents to communicate locally with one another and with their surroundings. In this paper, we propose a novel approach based on combining the characteristics of the two algorithms: Cat Swarm Optimization (CSO) and the Shuffled Frog Leaping Algorithm (SFLA). The experimental results show the convergence ratio of our hybrid SFLA-CSO algorithm is seven times higher than that of CSO and five times higher than the convergence ratio of the standard SFLA algorithm. The obtained results also revealed that the hybrid method speeds up the convergence significantly, and reduces the error rate. We compared the proposed hybrid algorithm against the famous relevant algorithms PSO, ACO, ABC, GA, and SA; the results are valuable and promising.

Cloud computing is a novel technology that provides users with better opportunities to gain access to services on the Internet. Users should utilize organizational services to meet their needs. They can also benefit from non-organizational services with high capacity but limited security. This study aims to provide a new security model that addresses security requirements for tasks and data as well as security strength for resources and communication paths. The proposed security model is defined security distance concept. Minimizing security distance has to do with task scheduling so that the resources can be matched with the security level and the data will be fitted into the appropriate communication path. The proposed scheduling algorithm takes the server profit into account in addition to the minimum security distance. The increased server profits can lead to higher resource sharing by the servers. The proposed scenario is implemented based on a neighborhood to search depth in task scheduling. This algorithm utilizes a novel ‘far and near neighborhood’ approach to select the best particle position. The approach generates both diversity and convergence in the set of answers. Finally, the proposed algorithm is compared with three other similar scheduling algorithms obtained by VNPSO, MPSO and NSGAII, considering the security of the cloud computing environment. The computational results show the effectiveness of the proposed algorithm to obtain resources with similar security and higher server profits.

Railguns has been researched considerably in recent years. Most of these researches is done to improve the main features of railgun, such as, increment of gradient of inductance L′, more uniform current density distributions, and launch synchronously multi projectiles per shot. In this paper, first the slice-rail railgun is presented and simulated by ANSYS software. Then, double and quad slice-rail with one axial is presented for multi-projectile shooting. Finally, the complete case of this slice-rail structure is studied as coaxial railgun. The geometry of slice-rail railgun has inner rail radii (Ri) and width (R1), outer rail radii (Ro) and width (R2) and the total angle of curved rails (θ). Current density distribution, Magnetic flux density and inductance gradient are computed for slice and coaxial railgun. Magnetic field at the outside of the muzzle for slice railgun with θ =90˚ is computed and compared with rectangular railgun meanwhile L′ equals to 0.45 μH/m for both railguns.

The Time Synchronized Channel Hopping (TSCH) mode of IEEE 802.15.4e has been widely used as an access method for the industrial Internet of Things (IoT). It permits to overcome the performance limits of 802.15.4 standard in such networks. It provides bounded latency and increased network capacity while mitigating the effects of interference and multipath fading. In this paper, we tackle two critical concerns of industrial networks, namely end-to-end reliability and delay by proposing two centralized scheduling mechanisms; First, the Height-based Scheduling (HS) that computes the schedule only based on the network topology. Second, T2AS, which takes into account both traffic demand and network topology to calculate the schedule. The later mechanism uses a composite weighting function that allows scheduling links with more load and longer distance from the root in earlier timeslots. This prioritizes the flows with more traffic to be scheduled earlier. Both algorithms provide subsequential scheduling for multi-hop scenarios. Simulation results, obtained from the OpenWSN emulator, particularly confirm the efficiency of T2AS in terms of reliability and end-to-end latency. More precisely, it guarantees a reliability of more than 99% for all network sizes. Furthermore, T2AS provides a noticeable bounded delay by delivering data packets within a single slotframe.

A novel design approach to construct a fault-tolerant control (FTC) system for a class of nonlinear systems based on a generalized Takagi-Sugeno (GT-S) fuzzy model is proposed. The local rules of the GT-S fuzzy model consist of some multiplicative nonlinear terms. The nonlinear system is affected by actuator faults and unknown disturbances. A state/fault observer is designed and then, a dynamic output feedback scheme is proposed based on the estimated fault and state information. The sufficient conditions for observer and controller design are separately given in terms of linear matrix inequalities (LMIs). It can be shown that the number of LMIs and the computational burden is less than that of similar methods and the effectiveness of the proposed dynamic output feedback FTC approach is verified by proposing simulation results applied to an inverted pendulum system.