Design and Analysis of OFDM System for Powerline Based Communication

Research on digital communication systems has been greatly developed in the past few years and offers a high quality of transmission in both wired and wireless communication environments. Coupled with advances in new modulation techniques, Orthogonal Frequency Division Multiplexing (OFDM) is a well-known digital multicarrier communication technique and one of the best methods of digital data transmission over a limited bandwidth [1]. In this paper, design and analysis of OFDM system for powerline based communication is proposed. In doing so, MATLAB and embedded Digital Signal Processing (DSP) systems are used to simulate the operation of virtual transmitter and receiver. The performance of the system design is then analysed by adding noise (additive white Gaussian noise, Powerline coloured background noise and Middleton Class A noise) in an attempt to corrupt the signal. In this paper results will show that performance is improved by using lower order modulation formats e.g. Binary Phase Shift Keying (BPSK), QPSK, etc. compared to the higher modulation schemes e.g. 64 Quadrature Amplitude Modulation (QAM); as they offer lower data rates but are more robust in the presence of noise. The performance study of OFDM scheme is also examined with and without presence of noise and application of forward error correction (FEC)

Design and Analysis of OFDM System for Powerline Based Communication

Research on digital communication systems has been greatly developed in the past few years and offers a high quality of transmission in both wired and wireless communication environments. Coupled with advances in new modulation techniques, Orthogonal Frequency Division Multiplexing (OFDM) is a well-known digital multicarrier communication technique and one of the best methods of digital data transmission over a limited bandwidth. The main aim of this research is to design an OFDM modem for powerline-based communication in order to propose and examine a novel approach in comparing the different modulation order, different modulation type, application of Forward Error Correction (FEC) scheme and also application of different noise types and applying them to the two modelled channels, Additive White Gaussian Noise (AWGN) and Powerline modelled channel. This is an attempt to understand and recognise the most suitable technique for the transmission of message or image within a communication system. In doing so, MATLAB and embedded Digital Signal Processing (DSP) systems are used to simulate the operation of virtual transmitter and receiver. The simulation results presented in this project suggest that lower order modulation formats (Binary Phase Shift Keying (BPSK) and 4-Quadrature Amplitude Modulation (QAM)), are the most preferred modulation techniques (in both type and order) for their considerable performance. The results also indicated that, Convolutional Channel Encoding (CCE)-Soft and Block Channel Encoding (BCE)-Soft are by far the best encoding techniques (in FEC type) for their best performance in error detection and correction. Indeed, applying these techniques to the two modelled channels has proven very successful and will be accounted as a novel approach for the transmission of message or image within a powerline based communication system

A Qualitative Study of Various Aspects of the Application of IoT in Disaster Management

Considering the vital issue of disaster management and the requirement of its additional development due to the increase in the rate of disasters over the recent years, using new technologies in all stages of disaster management including preparation stages for pre-disaster periods, reaction to disaster during its occurrence as well as the post-disaster reconstruction is very important. Therefore, the capacity of IoT in creating intelligence in objects to investigate different environmental parameters, the capacity of analyzing information, the intelligence required to predict some events and consequently, responding timely to any event and even proposing programs and systems for human performance are very effective in managing disasters. The existing resources for investigating the usages of Internet of Things (IoT) in disaster management could each address a particular aspect of this application. This paper has attempted to present a comprehensive view regarding the different dimensions of application of IoT in disaster management. The advantages and disadvantages of this application are mentioned, some instances of previous systems and models have also been discussed. The novelty of this work is the extent of examined dimensions and also addressing what can be done in different kinds of disasters

Design and Implementation of Efficient Smart Lighting Control System with Learning Capability for Dynamic Indoor Applications

Accurate and efficient adjustment of luminaire’s dimming level in a smart environment can be a huge challenge. Indoor lighting system as a nonlinear and time variant block, which consumes significant amount of electrical power is evaluated in this paper. In doing so, a control method is proposed to efficiently adjust luminaire’s dimming level in a smart environment and to optimize energy and user’s comfort level. The proposed control method takes advantages from neural network and its learning capabilities. In this research, photodetectors are placed at the work zones, where work zones can have different number of photodetectors without any increase in complexity and any adverse effect on the control system. The method is capable of adopting itself to daylight variations with high accuracy. A state machine is developed to implement the method. The method is implemented in MATLAB and lighting conditions are extracted in DIALux. Luminaire’s dimming levels are determined with accuracy higher than 99%. Daylight is considered as a bias to the system and thus the network does not need to be trained by any variations. In a dynamic condition, when taking into account the variation in daylight, the system mean error does not exceed 3%

Illumination Control of Smart Indoor Lighting Systems Consists of Multiple Zones

Accurate and power efficient determination of luminaires dimming level is a challenging issue in smart indoor lighting systems, since the lighting system is nonlinear and time variant. In this paper, a smart and power efficient control method is developed in order to determine luminaires dimming level in an indoor environment with multiple work zones. A positive point of the proposed control method is that photodetectors are placed at the work zones which increase the accuracy. Besides, different number of photodetectors can be placed at work zones in the proposed control method, since work zones may have different dimensions and also accuracy levels may differ. The control method takes the advantages of learning method to avoid complexity and also increase system reliability. The system can properly work with daylight variation during the daytime. Case studies are implemented in DIALux and the control method is evaluated in MATLAB. It is shown that the error for static condition is below 1% and for dynamic condition which daylight varies during daytime is increases to 5.6%

Zone Based Control Methodology of Smart Indoor Lighting Systems Using Feedforward Neural Networks

A smart, accurate, and energy efficient control strategy to adjust dimming level of luminaires in an indoor environment is proposed in this paper. The control block in lighting system is nonlinear and time variant, since multiple reflections of objects and daylight variation are related to daytime and they can directly affect the system. According to the complexity of equations which model the lighting system, a control system based on Neural Network (NN) and learning machine is developed. By considering each zone as an independent structure, occupancy in each zone is added. In addition, photodetectors are placed at the work zones and hence increasing the accuracy. The occupancy condition for other zones in the environment are considered as bias to the inputs of the system. Therefore, multiple reflections in the environment are considered in the design of the proposed control method. Accuracy and system performance is improved by separation of control block for each zone as an autonomous control unit, whereas complexity of the system is reduced. The proposed design is evaluated in test beds developed using DIALux and MATLAB. The mean error varies according to the effect of zones on each other. The method is suitable for indoor environment that zones does not have common luminaires. The mean error in the case study that is not proper for the method does not exceed 20%. Although, the error seems to be high but compared to the methods that have ceiling mount sensors is accurate and power and power efficient. Besides, the case with zones that has separated luminaires the mean error is less than 5%

The application of electromagnetic measurements for the assessment of skin passed steel samples

This paper begins by exploring the relationship between magnetic properties such as coercive field, RMS Magnetic Barkhausen Noise (MBN), initial and differential permeability and percentage elongation of skin passed samples for three different steels; interstitial free, micro alloyed and dual phase. A closed magnetic loop system is used to measure the fundamental magnetisation properties and a system based on an impedance analyser and a cylindrical coil is used to determine low field differential permeability. The results show that coercive field increases consistently with increasing percentage elongation for all three steels, as increasing material hardness causes an increase in magnetic hardness and a corresponding increase in coercive field. This effect levels off at higher values as dislocation density saturates. As would be expected, the inverse trend is observed for differential permeability. Similar results are also reported for MBN and initial and low field differential permeability measurements for the interstitial free and dual phase steel, but the behaviour for the micro alloyed samples appears to be more complex. Finally, the paper considers the response of two on-line measurement systems that exploit these magnetic relations. The first system applies pulse excitation and measures the resulting remnant magnetisation and the second analyses the harmonic response from AC excitation. Both systems can detect microstructural changes associated with varying magnetic properties during strip production

Analysis and design of defected ground structure for EMC improvement in mixed-signal transceiver modules

In this research, the return path discontinuity (RPD), located under the power amplifier (PA) substrate, of X-band transceiver module (Base), mounted on a four-layer printed circuit board (PCB), is investigated to improve the signal integrity by reducing the difference in the reference potential. This study is performed by initially employing the wirebond method, through the assessment of both numbers and sizes of bondwires by advanced design system (ADS). Six bondwires of 25 µm are added, producing an improvement of 6.82 dB for the reflection coefficient and 1.19 dB for the isolation and insertion loss. For further improvement, spiral shape defected ground structure (DGS) is implemented in the inner ground layer (layer 2) without using bond wires. The DGS simulation results illustrate an improvement of 3 dB for S11 and 0.6 dB for S12. To improve the electromagnetic compatibility (EMC), the authors propose combination and integration of both wirebond and DGS methods, called wirebond–DGS method, which results in an improvement of 11.86 dB for S11, 1.34 dB for S12 and S21, and 12.03 dB for S22. Finally, the wirebond–DGS RF module was fabricated and the measurement results exhibit an improvement of 8.07 dB for S11 and 9.39 dB for S22 in comparison with the fabricated Base module. In addition, 0.53 dB improvement for both S12 and S21 is also achieved