نشریه مهندسی مخابرات جنوب
پیاپی 42 (زمستان 1400)

In this review article, we aim to describe recent advances in compressive sensing-based data aggregation techniques in wireless sensor networks, including current research efforts, challenges, and research trends. Sparse and compressible signals are present in many applications of sensor networks, such as environmental monitoring and vehicle surveillance. Compressive sensing has many properties such as simplicity of sensing and compression operations, universality, and an acceptable decrease in the quality of signal reconstruction, which makes it attractive for use in sensor networks. Packet drops do not damage the network as much as other protocols, and only for each measurement that does not reach the sink will cause a slight decrease in the quality of signal reconstruction. We begin the discussion with a brief introduction to compressive sensing theory and then describe the use of this technique in wireless sensor networks. Finally, the research issues and challenges ahead are discussed to provide a perspective for future research

With the widespread use of WIFI networks, access location optimization is needed to improve network performance in the buildings. Wave propagation inside the building is one of the most challenging issues in network design and optimal location. Different parts of the building have different effects on the propagation of waves inside the building, such as fading, scattering and propagation of waves in several directions. Due to the nature of electromagnetic waves, the metal parts of the building have a great effect on the propagation of waves. In this paper, the effect of different metal parts of the building, including beams and door and window frames in standard dimensions, on the propagation of WIFI waves using Ray Tracing algorithm and CST software is modeled, and propagation patterns for different angles and distances are obtained. With the using of CST software, various modes such as rooms with different dimensions can be modeled. Then, based on the results, calculate the best location for the receiver. The results show that this method provides better capabilities than statistical methods to determine the best location of the receiver in the building.

Due to the many applications of DC to DC converters in electronics, regulating their output voltage is very important. In many applications it is necessary to change the DC voltage from one level to another. DC -DC converters are used for this purpose. The conversion of DC voltage from one level to another is done by switching elements such as transistors and diodes. Recently, the control of these converters has found a special place in scientific texts. Therefore, one of the objectives of this paper is to control and regulate the output voltage of the converter. The controller proposed in this paper to control the DC voltage level of the converter output is an optimized neural network controller with an algorithm based on colonial competition. The proposed controller function is that first the neural network is designed according to the expected goals of the system and then it is optimized by determining a suitable multi-objective benchmark function using the network structure optimization algorithm. This improves the performance of the control system. Because the proper selection of design parameters has a great role in the performance of the neural network that plays the role of controller. The proposed neural network function is to apply the appropriate signal transducer (PWM signal) to the switching elements in order to increase the performance. The results compared to the PID controller indicate the superiority of the proposed method.

The pervasive nature of social networking platforms has led to the production of large amounts of data. The lack of restrictions on information sharing on these networks allows information to be spread regardless of their validity. Such misinformation usually leads to the production and dissemination of rumors. Therefore, automatic detection of rumors on social networks is one of the attractive research areas for the analysis of these networks. This paper introduces a way to deal with the spread of rumors on social media based on the autoencoder neural network model and the ILSR epidemic dissemination model. Here, the autoencoder neural network model is applied with several innovative thresholds for initial rumor detection and then rumor control is performed by an extended version of the ILSR epidemic outbreak model. The proposed model called ILSHR considers social network users in five groups: Ignorant, Lurker, Spreader, Hibernator, and Removal. According to the transmission modes in the ILSHR rumor model, in addition to the characteristics of the lurker group, this model also considers the characteristics of the hibernator group of the SIHR model. Mechanisms of forgetfulness and reminders of hibernation can delay the rumor terminal time and ultimately reduce the impact of the rumor on the social network. The proposed method for modeling the spread of rumors has been performed on the Sina Weibo social network dataset. The results show better performance of the proposed method with 95.7% detection accuracy compared to DGRU and DLSTM models.

Realizing a cosecant-squared pattern is a challenging research area due to its widespread use in air-surveillance radar systems wherein the radiation characteristics of the tracking antenna play a significant role in accurate tracking of the targets. However, little research has been performed on realizing a cosecant-squared pattern in leaky-wave antennas (LWAs). In this paper, the authors present a synthesis procedure for realizing a cosecant-squared pattern in LWAs using optimization. To achieve the cosecant-squared pattern, the antenna is divided into sections each with an appropriate length, periodicity, and leakage rate. The length of the sections is determined such that all the sections have the same directivity. Moreover, following the appropriate layout for the beam pointing angle of the sections, the periodicity of the sections is obtained. The objective then is to determine the values of the leakage rate. This objective is achieved using optimization, which in this study is a genetic algorithm. To this end, through defining a proper cost function, the objectives are determined following the proposed optimization procedure. The procedure is described within a substrate integrated waveguide (SIW) LWA. A prototype of the antenna is fabricated and measured. Apart from the good agreement between the simulation and the measurement results, the proposed synthesis procedure can provide a target pattern with low ripples in the shaped region (≤ 2 dB) and a low level of side lobes (≤ -18 dB), making the antenna suitable for air-surveillance radar systems.

The use of renewable energy sources imposes new challenges on the electricity grid. This is mainly due to the variable nature and uncertainty of this type of resources. When the generation of renewables exceeds local demand, it may cause a reverse power flow in the feeder distribution. Reverse power flow may cause voltage rise and improper operation of voltage regulators. In this paper, a method for voltage regulation is proposed by using storage devices, variable generation of distributed generation sources and control devices. A strategy has been proposed for coordination between the various voltage regulating device. In the coordination method, the aim is to improve the system voltage profile while minimizing losses during the operation period. Genetic optimization method has been used to solve the problem and achieve the optimal solution, ie minimum voltage changes and minimum feeder losses. The proposed method is implemented in IEEE 123 bus test network in MATLAB software environment. Analysis of the results showed that the presence of photovoltaic sources reduces energy losses and the losses of the distribution system decrease with increasing photovoltaic size. The results also show that as the penetration level of photovoltaic sources increases, the voltage increases further and more tap changing and SVR changes are required to maintain the voltage. It was also proved that turning on the capacitor bank switch improves the voltage profile and the use of storage devices maximizes system security.