69 research outputs found

    Efficient channel equalization algorithms for multicarrier communication systems

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    Blind adaptive algorithm that updates time-domain equalizer (TEQ) coefficients by Adjacent Lag Auto-correlation Minimization (ALAM) is proposed to shorten the channel for multicarrier modulation (MCM) systems. ALAM is an addition to the family of several existing correlation based algorithms that can achieve similar or better performance to existing algorithms with lower complexity. This is achieved by designing a cost function without the sum-square and utilizing symmetrical-TEQ property to reduce the complexity of adaptation of TEQ to half of the existing one. Furthermore, to avoid the limitations of lower unstable bit rate and high complexity, an adaptive TEQ using equal-taps constraints (ETC) is introduced to maximize the bit rate with the lowest complexity. An IP core is developed for the low-complexity ALAM (LALAM) algorithm to be implemented on an FPGA. This implementation is extended to include the implementation of the moving average (MA) estimate for the ALAM algorithm referred as ALAM-MA. Unit-tap constraint (UTC) is used instead of unit-norm constraint (UNC) while updating the adaptive algorithm to avoid all zero solution for the TEQ taps. The IP core is implemented on Xilinx Vertix II Pro XC2VP7-FF672-5 for ADSL receivers and the gate level simulation guaranteed successful operation at a maximum frequency of 27 MHz and 38 MHz for ALAM-MA and LALAM algorithm, respectively. FEQ equalizer is used, after channel shortening using TEQ, to recover distorted QAM signals due to channel effects. A new analytical learning based framework is proposed to jointly solve equalization and symbol detection problems in orthogonal frequency division multiplexing (OFDM) systems with QAM signals. The framework utilizes extreme learning machine (ELM) to achieve fast training, high performance, and low error rates. The proposed framework performs in real-domain by transforming a complex signal into a single 2–tuple real-valued vector. Such transformation offers equalization in real domain with minimum computational load and high accuracy. Simulation results show that the proposed framework outperforms other learning based equalizers in terms of symbol error rates and training speeds

    High-Performance Parallel Implementation of Genetic Algorithm on FPGA

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    Genetic algorithms (GAs) are used to solve search and optimization problems in which an optimal solution can be found using an iterative process with probabilistic and non-deterministic transitions. However, depending on the problem’s nature, the time required to find a solution can be high in sequential machines due to the computational complexity of genetic algorithms. This work proposes a full-parallel implementation of a genetic algorithm on field-programmable gate array (FPGA). Optimization of the system’s processing time is the main goal of this project. Results associated with the processing time and area occupancy (on FPGA) for various population sizes are analyzed. Studies concerning the accuracy of the GA response for the optimization of two variables functions were also evaluated for the hardware implementation. However, the high-performance implementation proposed in this paper is able to work with more variable from some adjustments on hardware architecture. The results showed that the GA full-parallel implementation achieved throughput about 16 millions of generations per second and speedups between 17 and 170,000 associated with several works proposed in the literature

    Wavelet Theory

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    The wavelet is a powerful mathematical tool that plays an important role in science and technology. This book looks at some of the most creative and popular applications of wavelets including biomedical signal processing, image processing, communication signal processing, Internet of Things (IoT), acoustical signal processing, financial market data analysis, energy and power management, and COVID-19 pandemic measurements and calculations. The editor’s personal interest is the application of wavelet transform to identify time domain changes on signals and corresponding frequency components and in improving power amplifier behavior

    Review on Multi Level Inverter Topologies and Control Strategies for Solar Power Conversion

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    Nowadays solar power has become an alternate method of power generation for standalone systems for both urban and rural electrification. The Power Electronics converters used for the power conversion should provide quality AC output to have near sinusoidal voltage. The inverter topology and the PWM technique of the inverter play a vital role in providing quality output. This paper reviews recent contribution to establish the current status and development of the technology to provide reader with an insightful review of multilevel inverters and its control strategy. A brief overview of Multi Level Inverters (MLI) topology and advantages of Cascaded H-Bridge Multi Level Inverter (CHBMLI) for solar power conversion is presented and the various control strategies for CHBMLI are discussed with view point of quality output.  Among the different PWM techniques discussed, the Elliptical Multi Carrier PWM (EMC PWM) control strategy is the new modulation technique which successfully improves the DC bus utilization without over-modulation and without adding third harmonic to fundamental frequency. Also, the technique is successful in reducing the %THD at the output voltage. The control strategy is simple even with increased   level of output voltage, which is not possible in SVPWM technique.  Hence, the EMC PWM technique is having better performance when compared to Multi Carrier PWM (MCPWM) technique, Space Vector PWM (SVPWM) technique and Third Harmonic Injection PWM (THIPWM) technique.&nbsp

    Channel estimation techniques for filter bank multicarrier based transceivers for next generation of wireless networks

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    A dissertation submitted to Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering (Electrical and Information Engineering), August 2017The fourth generation (4G) of wireless communication system is designed based on the principles of cyclic prefix orthogonal frequency division multiplexing (CP-OFDM) where the cyclic prefix (CP) is used to combat inter-symbol interference (ISI) and inter-carrier interference (ICI) in order to achieve higher data rates in comparison to the previous generations of wireless networks. Various filter bank multicarrier systems have been considered as potential waveforms for the fast emerging next generation (xG) of wireless networks (especially the fifth generation (5G) networks). Some examples of the considered waveforms are orthogonal frequency division multiplexing with offset quadrature amplitude modulation based filter bank, universal filtered multicarrier (UFMC), bi-orthogonal frequency division multiplexing (BFDM) and generalized frequency division multiplexing (GFDM). In perfect reconstruction (PR) or near perfect reconstruction (NPR) filter bank designs, these aforementioned FBMC waveforms adopt the use of well-designed prototype filters (which are used for designing the synthesis and analysis filter banks) so as to either replace or minimize the CP usage of the 4G networks in order to provide higher spectral efficiencies for the overall increment in data rates. The accurate designing of the FIR low-pass prototype filter in NPR filter banks results in minimal signal distortions thus, making the analysis filter bank a time-reversed version of the corresponding synthesis filter bank. However, in non-perfect reconstruction (Non-PR) the analysis filter bank is not directly a time-reversed version of the corresponding synthesis filter bank as the prototype filter impulse response for this system is formulated (in this dissertation) by the introduction of randomly generated errors. Hence, aliasing and amplitude distortions are more prominent for Non-PR. Channel estimation (CE) is used to predict the behaviour of the frequency selective channel and is usually adopted to ensure excellent reconstruction of the transmitted symbols. These techniques can be broadly classified as pilot based, semi-blind and blind channel estimation schemes. In this dissertation, two linear pilot based CE techniques namely the least square (LS) and linear minimum mean square error (LMMSE), and three adaptive channel estimation schemes namely least mean square (LMS), normalized least mean square (NLMS) and recursive least square (RLS) are presented, analyzed and documented. These are implemented while exploiting the near orthogonality properties of offset quadrature amplitude modulation (OQAM) to mitigate the effects of interference for two filter bank waveforms (i.e. OFDM/OQAM and GFDM/OQAM) for the next generation of wireless networks assuming conditions of both NPR and Non-PR in slow and fast frequency selective Rayleigh fading channel. Results obtained from the computer simulations carried out showed that the channel estimation schemes performed better in an NPR filter bank system as compared with Non-PR filter banks. The low performance of Non-PR system is due to the amplitude distortion and aliasing introduced from the random errors generated in the system that is used to design its prototype filters. It can be concluded that RLS, NLMS, LMS, LMMSE and LS channel estimation schemes offered the best normalized mean square error (NMSE) and bit error rate (BER) performances (in decreasing order) for both waveforms assuming both NPR and Non-PR filter banks. Keywords: Channel estimation, Filter bank, OFDM/OQAM, GFDM/OQAM, NPR, Non-PR, 5G, Frequency selective channel.CK201

    Field Programmable Gate Arrays (FPGAs) II

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    This Edited Volume Field Programmable Gate Arrays (FPGAs) II is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of Computer and Information Science. The book comprises single chapters authored by various researchers and edited by an expert active in the Computer and Information Science research area. All chapters are complete in itself but united under a common research study topic. This publication aims at providing a thorough overview of the latest research efforts by international authors on Computer and Information Science, and open new possible research paths for further novel developments

    MATLAB

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    A well-known statement says that the PID controller is the "bread and butter" of the control engineer. This is indeed true, from a scientific standpoint. However, nowadays, in the era of computer science, when the paper and pencil have been replaced by the keyboard and the display of computers, one may equally say that MATLAB is the "bread" in the above statement. MATLAB has became a de facto tool for the modern system engineer. This book is written for both engineering students, as well as for practicing engineers. The wide range of applications in which MATLAB is the working framework, shows that it is a powerful, comprehensive and easy-to-use environment for performing technical computations. The book includes various excellent applications in which MATLAB is employed: from pure algebraic computations to data acquisition in real-life experiments, from control strategies to image processing algorithms, from graphical user interface design for educational purposes to Simulink embedded systems

    Performance Enhancement of Shunt APFs Using Various Topologies, Control Schemes and Optimization Techniques

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    Following the advent of solid-state power electronics technology, extensive usage of nonlinear loads has lead to severe disturbances like harmonics, unbalanced currents, excessive neutral current and reactive power burden in three-phase power systems. Harmonics lower down the efficiency and power factor, increase losses, and result in electromagnetic interference with neighbouring communication lines and other harmful consequences. Over the years, active power filter (APF) has been proven to be a brilliant solution among researchers and application engineers dealing with power quality issues. Selection of proper reference compensation current extraction scheme plays the most crucial role in APF performance. This thesis describes three time-domain schemes viz. Instantaneous active and reactive power (p-q), modified p-q, and Instantaneous active and reactive current component (i_d-i_q) schemes. The objective is to bring down the source current THD below 5%, to satisfy the IEEE-519 Standard recommendations on harmonic limits. Comparative evaluation shows that, i_d-i_q is the best APF control scheme irrespective of supply and load conditions. Results are validated with simulations, followed by real-time analysis in RT-Lab.In view of the fact that APFs are generally comprised of voltage source inverter (VSI) based on PWM, undesirable power loss takes place inside it due to the inductors and switching devices. This is effectively minimized with inverter DC-link voltage regulation using PI controller. The controller gains are determined using optimization technique, as the conventional linearized tuning of PI controller yield inadequate results for a range of operating conditions due to the complex, nonlinear and time-varying nature of power system networks. Developed by hybridization of Particle swarm optimization (PSO) and Bacterial foraging optimization (BFO), an Enhanced BFO technique is proposed here so as to overcome the drawbacks of both PSO and BFO, and accelerate the convergence of optimization problem. Extensive simulation studies and RT-Lab real-time investigations are performed for comparative assessment of proposed implementation of PSO, BFO and Enhanced BFO on APF. This validates that, the APF employing Enhanced BFO offers superior harmonic compensation compared to other alternatives, by lowering down the source current THD to drastically small values.Another indispensable aspect of APF is its topology, which plays an essential role in meeting harmonic current requirement of nonlinear loads. APFs are generally developed with current-source or voltage-source inverters. The latter is more convenient as it is lighter, cheaper, and expandable to multilevel and multistep versions for improved performance at high power ratings with lower switching frequencies. There can be different topologies of VSI depending on the type of supply system. With each topology, constraints related to DC-link voltage regulation change. For effective compensation, irrespective of the number and rating of DC-link capacitors used in any particular topology, voltages across them must be maintained constant with optimal regulation of DC-link voltage. Various topologies for three-phase three-wire systems (conventional two-level and multilevel VSIs) and four-wire systems (split-capacitor (2C), four-leg (4L), three H-bridges (3HB) and three-level H-bridge (3L-HB) VSIs) are analyzed and compared based on component requirements, effectiveness in harmonic compensation, cost and area of application

    A Survey of Blind Modulation Classification Techniques for OFDM Signals

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    Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent transceiver for future wireless communications. Blind MC has several applications in the adaptive and automated systems of sixth generation (6G) communications to improve spectral efficiency and power efficiency, and reduce latency. It will become a integral part of intelligent software-defined radios (SDR) for future communication. In this paper, we provide various MC techniques for orthogonal frequency division multiplexing (OFDM) signals in a systematic way. We focus on the most widely used statistical and machine learning (ML) models and emphasize their advantages and limitations. The statistical-based blind MC includes likelihood-based (LB), maximum a posteriori (MAP) and feature-based methods (FB). The ML-based automated MC includes k-nearest neighbors (KNN), support vector machine (SVM), decision trees (DTs), convolutional neural networks (CNNs), recurrent neural networks (RNNs), and long short-term memory (LSTM) based MC methods. This survey will help the reader to understand the main characteristics of each technique, their advantages and disadvantages. We have also simulated some primary methods, i.e., statistical- and ML-based algorithms, under various constraints, which allows a fair comparison among different methodologies. The overall system performance in terms bit error rate (BER) in the presence of MC is also provided. We also provide a survey of some practical experiment works carried out through National Instrument hardware over an indoor propagation environment. In the end, open problems and possible directions for blind MC research are briefly discussed
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