Showing papers on "Digital signal published in 2021"

High-Utilization, High-Flexibility Depth-First CNN Coprocessor for Image Pixel Processing on FPGA

Abstract: Recently, CNNs are increasingly exploited for pixel processing tasks, such as denoising, which opens up new challenges due to the increased activation and operation count. This article presents a CNN coprocessor architecture to solve these challenges on field-programmable gate array (FPGA) through four main contributions. First, the I/O communication between the host processor and the FPGA is reduced to a minimum using a depth-first (DF) principle. Three new DF approaches are presented. Second, to ensure high throughput, the increased parallelization opportunities of the proposed line-based DF operation are analyzed. Third, introducing programmability to the compute array is introduced to enable a broad deployment while maintaining high utilization of the available multipliers digital signal processings (DSPs), independently of the kernel dimensions and without control of the host processor. This is in contrast with many state-of-the-art FPGA implementations, focusing on only one algorithm and/or one kernel topology. Fourth, a model is built to investigate the influence of architecture parameters and show the benefits of DF. The scalable design can be deployed on a wide range of FPGAs, maintaining 78%–93% DSP utilization across all algorithms (denoising, optical flow, depth estimation, segmentation, and super-resolution) and FPGA platforms. Up to 695 GOPS is achieved on a Zynq XCZU9EG board, matching state-of-the-art performance with a more flexible design. The throughput is compared with other pixel processing architectures on FPGA.

Channel Estimation for 6G V2X Hybrid Systems Using Multi-Vehicular Learning

Abstract: Channel estimation for hybrid Multiple Input Multiple Output (MIMO) systems at Millimeter-Waves/sub-THz is a fundamental, despite challenging, prerequisite for an efficient design of hybrid MIMO precoding/combining. Most works propose sequential search algorithms, e.g., Compressive Sensing (CS), that are most suited to static channels and consequently cannot apply to highly dynamic scenarios such as Vehicle-to-Everything (V2X). To address the latter ones, we leverage recurrent vehicle passages to design a novel Multi Vehicular (MV) hybrid MIMO channel estimation suited for Vehicle-to-Infrastructure (V2I) and Vehicle-to-Network (V2N) systems. Our approach derives the analog precoder/combiner through a MV beam alignment procedure. For the digital precoder/combiner, we adapt the Low-Rank (LR) channel estimation method to learn the position-dependent eigenmodes of the received digital signal (after beamforming), which is used to estimate the compressed channel in the communication phase. Extensive numerical simulations, obtained with ray-tracing channel data and realistic vehicle trajectories, demonstrate the benefits of our solution in terms of both achievable spectral efficiency and mean square error compared to the unconstrained maximum likelihood estimate of the compressed digital channel, making it suitable for both 5G and future 6G systems. Most notably, in some scenarios, we obtain the performance of the optimal fully digital systems.

A Digital Signal Recovery Technique Using DNNs for LEO Satellite Communication Systems

Abstract: This article proposes a new digital signal recovery (DSR) technique for next-generation power efficient low Earth orbit (LEO) satellite-to-ground communication systems, which feature additive white Gaussian noise (AWGN) channel and significant power variation. This technique utilizes the prior knowledge [i.e., nonlinearities of radio frequency power amplifiers (RF-PAs)] of space-borne transmitters to improve the quality of the signal received at ground stations by modeling and mitigating the imperfection using deep neural networks (DNNs). Benefiting from its robustness against noise and power variation, the proposed DNN based DSR technique (DNN–DSR), can correct high signal distortions caused by the nonlinearities and hence allows RF-PAs to work close to their saturation region, leading to a high power efficiency of the LEO satellites. This work has been validated by both simulations and experiments, in comparison with the power back- off technique as well as memory polynomial-based DSR solutions. Experimental results show that the DNN–DSR technique can increase the drain efficiency of the space-borne RF-PA from 32.6% to 45% while maintaining the same error vector magnitude as the power back- off technique. It has also been demonstrated that the proposed DNN–DSR technique can handle a signal power variation of 12 dB, which is challenging for conventional solutions.

Chaos Synchronization Based on Hybrid Entropy Sources and Applications to Secure Communication

Abstract: We experimentally demonstrate a chaotic synchronization scheme based on the electro-optic hybrid entropy sources. The chaos synchronization method is experimentally validated that 200 km high-level chaos synchronization can be attained and the distance can be further extended. The digital signal induced chaos synchronization signal has good robustness against the potential distortions in long-haul optical transmission. On the basis of the digital signal induced chaos synchronization strategy, a correlated random bit generation (CRBG) scheme with bit rate of 1.25 Gb/s and distance of 200 km is proposed. The generated correlated random bit sequences (CRBSs) pass all the NIST tests. Meanwhile, a data encryption scheme based on the robust chaos synchronization method is proposed with low computation complexity. The synchronization signal, in which the encrypted data is embedded, maintains the strength in long-haul transmission. The strong robustness of the scheme under parameter mismatch is numerically analyzed. These propositions show great potential in the field of secure communication, especially the long-haul scenario.

Digital Signal Multi-Stage Discrete Fourier Transform and Its Practical Applications

Abstract: The issues related to the study of the problem of minimizing hardware costs for software and hardware implementation of algorithms for frequency selection of digital signals on programmable logic devices are considered. The purpose of the study is to define the theoretical foundations of the concept and methodology of the multi-stage discrete Fourier transform without performing multiplication operations. The methods of software and hardware modeling of digital signal processing algorithms were used in the study. The principles of the multi-stage discrete Fourier transform of complex signals are specified only by the operations of adding their time samples. Its methods and digital algorithms are presented. Their basic formulas are given.

Digital-Analog Hybrid Optical Access Integrating 56-Gbps PAM-4 Signal and 5G mmWave Signal by Spectral Null Filling

Abstract: A bandwidth-efficient and low-cost spectral-null-filling scheme simultaneously delivering a 56-Gbps 4-level pulse amplitude modulation (PAM-4) digital signal and a 10 × 400-MHz analog radio frequency (RF) signal on a single wavelength is demonstrated for high-capacity wired and wireless optical access networks. The data rate of the PAM-4 signal is consistent with the next-generation passive optical network (PON), and the PAM-4 signal inherently provides a spectral null at 28 GHz, which can be filled with the RF signal exactly at the 5G-specified millimeter wave (mmW) band. Since pulse shaping is not essential in this hybrid transmission system, a low-cost 2-bit digital-to-analog converter (DAC) is adopted for the PAM-4 signal generation. Volterra nonlinear equalizer is adopted to effectively eliminate the analog-to-digital crosstalk without reserving a frequency gap in between. The digital-analog hybrid signal is simultaneously transmitted over a 25-km standard single-mode fiber in telecom C-band and the impact of chromatic dispersion on the number of supported mmW bands is analyzed. In addition, three types of hybrid transmitters are experimentally demonstrated, among which the first-time proposed IQ-modulator-based hybrid transmitter shows the best performance.

Digital communication using a cyclic level scheme in an atomic radio-over-fiber device

Abstract: We experimentally demonstrate binary phase-shift keying and multi-stage four phase shift keying of a microwave carrier and its corresponding demodulation in the optical regime using room temperature Rb atoms. We use a cyclic three-level scheme in 85Rb atoms to achieve this. The importance of our scheme is that the cyclic, closed interaction of the atomic levels with electromagnetic fields makes our system inherently sensitive to the phase of the microwave field. This enables our system to directly encode a phase modulated digital signal in the microwave field and decode it as intensity modulation in the optical field. We measure the correlation of our demodulated optical signal with an ideal template and establish a viable signal bandwidth of about 1 MHz. Our atomic scheme also enables phase dependent amplification of the demodulated optical signal through a hybrid second order nonlinearity. This phase dependent atomic antenna has inherent features of demodulation, radio-to-optical conversion, and amplification. The ground states used in our scheme are quantum memory storage spin states, which makes our scheme inherently suitable for applications involving communication and storage and retrieval of quantum signals.

Features of Bijection of Spaces when Transmitting Messages from Source to Recipient

Abstract: Signals from the source of messages can be different, and to describe them, appropriate models are used, which make it possible to represent the generated signals in various metric spaces that are adequate to the type of signals under consideration. For example, the Euclidean space is used to describe analog signals, while the Hamming space is used to describe a discrete digital signal. The article discusses the features of bijections of the Hamming and Euclidean spaces. Matrices of code distances for the Gray and Natural codes are constructed. Tables of distortions in code combinations and tables of transitions of code combinations from one to another for two types of coding are given. The results obtained show certain advantages of the Gray code in comparison with the Natural code.

Ultra-high speed random bit generation based on Rayleigh feedback assisted ytterbium-doped random fiber laser

Abstract: In this paper, we propose an ultra-high speed random bit generator without the time-delay signature based on an ytterbium-doped random fiber laser (YRFL) with Rayleigh scattering feedback. The spectrum of the YRFL has a relatively broad bandwidth (0.35 nm) and the lasing temporal intensity shows random fluctuations without cavity induced time-delay signatures (TDS), which are essential for ultra-high speed random bit generation. The chaotic signal and its time-delayed signal sampling at 40 Giga samples per second (GS/s) are converted to digital 8-bit signals. By selecting 5 least significant bits from each 8-bit digital signal and using bitwise exclusive-OR operation, we experimentally achieve 200 Gbps physical random bit generation based on ytterbium-doped random fiber laser with the verified randomness. The combination of broadband emission and free of TDS makes random fiber lasers new promising sources for high performance random bit generation in a simple and compact configuration, which has a great potential in cryptography and secure communication applications.

Developing digital signal clustering method using local binary pattern histogram

Abstract: In this paper we presented a new approach to manipulate a digital signal in order to create a features array, which can be used as a signature to retrieve the signal. Each digital signal is associated with the local binary pattern (LBP) histogram; this histogram will be calculated based on LBP operator, then k-means clustering was used to generate the required features for each digital signal. The proposed method was implemented, tested and the obtained experimental results were analyzed. The results showed the flexibility and accuracy of the proposed method. Althoug different parameters of the digital signal were changed during implementation, the results obtained showed the robustness of the proposed method.

Deep Digital Signal Recovery for LEO Satellite Communication in Presence of System Perturbations

Abstract: This paper proposes a deep neural network (DNN)-based digital signal recovery (DSR) technique for low Earth orbit (LEO) satellite communications. Different from existing work, which only investigates impacts of the satellite-to-ground communication channel, this work focuses on handling the nonlinearity variations caused by input power level perturbations in the transmitter. The system is validated using a high gain radio frequency power amplifier (RF-PA) operating at 28.5 GHz, where perturbations are introduced by varying the power level of the input signal, from −39 dBm to −31 dBm, to the RF-PA. Experimental results show that the DNN trained at an input power level of −35 dBm achieved an improvement of 7.52 dB in the adjacent channel leakage ratio (ACLR), and an improvement of 4.2% in error vector magnitude (EVM). Applying the DDN trained at −35 dBm to other cases demonstrates that a 1 dB power level perturbation only leads to ≈ 1 dB degradation of the ACLR and ≈ 1.6% degradation of the EVM, respectively, which indicates the potential of the proposed approach.

A Signal Quality Monitoring Algorithm Based on Chip Domain Observables for BDS B1C Signal

Abstract: Evil waveforms (EWFs) could be considered as anomalous signals from the analog and/or digital signal generating hardware on board with imperfections or failures, and might introduce hazardous misleading information (HMI) to users. Since the first observed EWF occurrence, i.e. SVN-19 Event in 1993 [1], a series of techniques called signal quality monitoring (SQM) have been developed and implemented in currently running SBAS’s. Conventional SQM, represented by SQM2b, was based on multicorrelator detection techniques. However, there exist some obvious and potential limitations or disadvantages on it. To mitigate all these problems, SQM algorithms based on chip domain observables (CDOs) are emerging. The third generation of BDS has been officially declared to provide global services on positioning, navigation and timing at the end of July 2020, while BDSBAS is under development, aiming at providing DFMC SBAS services under realistic requirement of high inter-operability. This paper proposes an SQM algorithm based on CDOs, to explore the effectiveness of chip-shape detection technique for normalized DFMC SBAS SQM on BOC signals. Detailed descriptions of the proposed algorithm and evaluation scheme with CDOs obtention, thresholds derivation and process of detection are expounded. In addition, simulations on BDS B1C signal (BOC(1,1) modulated) are carried out, and analyses on varies aspects are presented for confirmation of correctness and validity.

Robust Digital Signal Recovery for LEO Satellite Communications Subject to High SNR Variation and Transmitter Memory Effects

Abstract: This paper proposes a robust digital signal recovery (DSR) technique to tackle the high signal-to-noise ratio (SNR) variation and transmitter memory effects for broadband power efficient down-link in next-generation low Earth orbit (LEO) satellite constellations. The robustness against low SNR is achieved by concurrently integrating magnitude normalization and noise feature filtering using a filtering block built with one batch normalization (BN) layer and two bidirectional long short-term memory (BiLSTM) layers. Moreover, unlike existing deep neural network-based DSR techniques (DNN-DSR), which failed to effectively take into account the memory effects of radio-frequency power amplifiers (RF-PAs) in the model design, the proposed BiLSTM-DSR technique can extracts the sequential characteristics of the adjacent in-phase (I) and quadrature (Q) samples, and hence can obtain superior memory effects compensation compared with the DNN-DSR technique. Experimental validation results of the proposed BiLSTM-DSR with a 100 MHz bandwidth OFDM signal demonstrate an excellent performance of 11.83 dB and 9.4% improvement for adjacent channel power ratio (ACPR) and error vector magnitude (EVM), respectively. BiLSTM-DSR also outperforms the existing DNN-DSR technique in terms of the ACPR and EVM by 2.4 dB and 0.9%, which provides a promising solution for developing deep learning-assisted receivers for high-throughput LEO satellite networks.

Convergence Analysis of Self-Adaptive Equalizers Using Evolutionary Programming (EP) and Least Mean Square (LMS)

Abstract: Digital communication has become an important part of our lives, and technology has been undergoing advancements With the arrival of the age of digitalization and digital signal, communication has got implemented in a vibrant range of applications but still, they are strongly affected by two basic problems, namely Noise and Inter-Symbol Interference (ISI) This is caused by the error-creating phenomena which are characteristics between the transmitter and receiver which include the scattering of the transmitted signal The noise produced in the communication channel is caused by channel characteristics and can be reduced with proper channel selection The SNR can be improved by improving the transmitter signal strength even in spite of noisy signal at the receiver By using the adaptive equalization in channels will reduce this effect drastically and can be implemented by using various adaptive algorithms Hence, an adaptive channel equalizer is used to inverse the effect channel had on the signal to get back the initial information There are many adaptive algorithms to update the coefficients of equalizers; evolutionary algorithms are used in this paper to do so The two algorithms used before are Artificial Bee Colony algorithm (ABC) and Ant Colony Optimization (ACO) The latest algorithm is the combination of Evolutionary Programming and LMS algorithm (EPLMS); this gives better solution faster A comparative study between the algorithms is done in this paper

System and method for processing electrophysiological signals

Abstract: An electrophysiology system including signal channels each of which processes an electrophysiological signal along a signal path extending from an input port that receives the analog electrophysiological signal, via an adjustable gain element that amplifies the electrophysiological signal, and via an ADC element that converts the analog signal into a corresponding digital signal, to an output port. The system further includes a monitoring element that generates a monitoring signal representative of a DC component of the electrophysiological signal and a gain control element that generates a control signal responsive to the monitoring signal. The control signal controls the gain setting of the gain element to cause a decrease in gain, if an increase in the magnitude of the DC component is determined; and/or an increase in gain, if a decrease in the magnitude of the DC component is determined.

An analysis of video signal using Double-ended mode in perspective of EMI

Abstract: High Definition Multimedia Interface(HDMI), the representative output device of computers, generally leaks unintended electromagnetic waves. However, not all frequency components of the digital signal are leaked out in a befitting state for reconstruction image. In this study, frequency components of video signals and frequency bands suitable for reconstruction image information are analyzed.

A Digital-Analog Hybrid System-on-Chip for Capacitive Sensor Measurement and Control.

Abstract: Sensors based on capacitance detection are common in the field of inertial measurement and have the potential for miniaturization and low power consumption. In order to control and process such sensors, a novel digital-analog hybrid system-on-chip (SoC) is designed and implemented. The system includes a capacitor to voltage (C/V) conversion circuit and a band-pass sigma-delta modulator (BPSDM) as the analog-to-digital converter (ADC). The digital signal is processed by the dedicated circuit module based on the least mean square error demodulation (LMSD) algorithm on the chip. The low-power Cortex-M3 processor supports software implementation of control algorithms and circuit parameter configuration. The control signal is output through a digital BPSDM. The chip was taped out under SMIC 180 nm Complementary Metal Oxide Semiconductor (CMOS) technology and tested for performance. The result shows that the maximum operating frequency of the chip is 105 MHz. The total area is 77.43 mm2. When the system clock is set to 51.2 MHz, the static power consumption and dynamic power consumption of the digital system are 18 mW and 54 mW respectively.

Audio Enhancement of Physical Models of Musical Instruments Using Optimal Correction Factors: The Recorder Case

Abstract: A simulation of a musical instrument is considered to be a successful one when there is a good resemblance between the model’s synthesized sound and the real instrument’s sound. In this work, we propose the integration of physical modeling (PM) methods with an optimization process to regulate a generated digital signal. Its goal is to find a new set of values of the PM’s parameters’ that would lead to a synthesized signal matching as much as possible to reference signals corresponding to the physical musical instrument. The reference signals can be: (a) described by their acoustic characteristics (e.g., fundamental frequencies, inharmonicity, etc.) and/or (b) the signals themselves (e.g., impedances, recordings, etc.). We put this method into practice for a commercial recorder, simulated using the digital waveguides’ PM technique. The reference signals, in our case, are the recorded signals of the physical instrument. The degree of similarity between the synthesized (PM) and the recorded signal (musical instrument) is calculated by the signals’ linear cross-correlation. Our results show that the adoption of the optimization process resulted in more realistic synthesized signals by (a) enhancing the degree of similarity between the synthesized and the recorded signal (the average absolute Pearson Correlation Coefficient increased from 0.13 to 0.67), (b) resolving mistuning issues (the average absolute deviation of the synthesized from the recorded signals’ pitches reduced from 40 cents to the non-noticeable level of 2 cents) and (c) similar sound color characteristics and matched overtones (the average absolute deviation of the synthesized from the recorded signals’ first five partials reduced from 41 cents to 2 cents).

Spectral representations of digital signals using non-binary Galois fields.

Abstract: The article shown that for digital signal processing varying in a limited range of amplitudes it is advisable to consider a set of signal levels through its mapping into certain Galois field, i.e., finite commutative body. In this case, the signal coding differs from binary, however, this creates quite definite advantages. In particular, a modified Walsh basis where the elements +1 and -1 are treated as elements of a non-binary Galois field can be used. The main difference of such use of the Walsh basis is that the elements of the Galois field corresponding to the spectral components belong to the same set as the original signal levels do. This provides a significant reduction in the amount of information when transmitting information about the signal, presented in the form of its spectrum. A specific example of using the Galois field for processing a time series of data that simulates a digital signal is presented

Deep intelligent spectral labelling and receiver signal distribution for optical links.

Abstract: A unique automatic receiver signal distribution strategy is proposed for private optical networks based on the concept of non-orthogonality. A non-orthogonal signal waveform can compress the spectral bandwidth, which not only fits a signal in a bandwidth limited scenario, but also enables the compression ratio information for labelling. Depending on a unique value of spectral compression, an end user destination can be correlated. A network edge node will rely on deep learning to intelligently identify each raw signal and forward it to corresponding end users with no sophisticated digital signal pre-processing. In this case, signal identification and distribution are faster while computationally intensive signal compensation and detection will be shifted to each end user since the receiver is highly dynamic and user-defined in private optical networks. An intelligent signal classifier will be trained considering various fiber transmission factors such as transmission distance, training dataset size and launch power. At the end, a universal classifier is obtained, which can be used to identify signals in a system for any fiber transmission distance and launch power.

High-Speed Digital Detector for the Internet of Things Assisted by Signal’s Intensity Quantification

Abstract: This paper proposes a high-speed digital detector for the Internet of Things (IoT) assisted by signal's intensity quantification. The detector quantifies the amplitude of each pixel of the detected image and converts it into a digital signal, which can be directly applied to the IoT with wireless communication system. Two types of amplitude quantization algorithms, uniform quantization and non-uniform quantization, are applied to the detector, which further improves the quality of the detected image and the robustness of the image signal in a noisy environment. Related simulations have been established to verify the accuracy of the models and algorithms.

Integrated communication link testing

Abstract: A test and measurement device includes an input configured to receive an analog signal from a Device Under Test (DUT), an Analog to Digital Converter (ADC) coupled to the input and structured to convert the analog signal to a digital signal, a receiver implemented in a first Field Programmable Gate Array (FPGA) and structured to accept the digital signal and perform signal analysis on the digital signal, a transmitter implemented in a second FPGA and structured to generate a digital output signal, and a Digital to Analog Converter (DAC) coupled to the transmitter and structured to convert the digital output signal from the transmitter to an analog signal, and structured to send the analog signal to the DUT. The receiver and the transmitter are coupled together by a high speed data link over which data about the current testing environment may be shared.

300GHz Terahertz Transmission Scheme Based on SFP Optical Fiber Module

Abstract: This paper presents a fusion of optical fiber transmission with terahertz wireless communication system scheme. One of a pair of SFP optical module is used to process the digital signal generated by AWG (arbitrary waveform generator), which is transmitted by optical fiber for long distance. Another SFP optical module completes the photoelectric conversion of the signal and inputs the signal to the terahertz frequency conversion module for wireless transmission. The code rate is 1.25 Gbps, the carrier frequency is 300 GHz and the modulation mode is QPSK. The results were observed through the eye diagram of the signal received by the oscilloscope. The quality of the eye diagram is well, which indicates that the terahertz over fiber wireless communication has practical significance for indoor high-speed access and other application scenarios.

Pulse Shape Discrimination for Online Data Acquisition in Water Cherenkov Detectors Based on FPGA/SoC

Abstract: Discrimination of secondary particles produced in extensive air showers is needed to study the composition of primary cosmic rays. High speed data acquisition and the increase in resources in modern FPGAs with the addition of a microprocessor in System-on-Chip (SoC) technologies allow to implement complex algorithms for digital signal analysis. Pulse shape Discrimination (PSD) can be carried out in real-time on the digital front-end of the detector; indeed online data analysis permits to save computational resources in post-processing and transmission bandwidth. We describe two methods for PSD, the first one based on artificial neural network (ANN) using the novel hls4ml package, and the other based on a correlation approach using finite impulse response (FIR) filters. Both methods were implemented and tested on Xilinx FPGA SoC devices ZU9EG Zynq Ultrascale+ and XC7Z020 Zynq. Data from a Water Cherenkov Detector (WCD) were acquired with a 500 Mhz, 8-bit high speed analog-to-digital converter acquisition system. Experimental results obtained with both methods are presented along with timing, accuracy and resources utilization analysis.

Total Ionizing Dose Effect and Failure Mechanism of Digital Signal Processor

Abstract: Ionizing radiation effect and failure mechanism of Digital signal processor (DSP) is studied through test-board and automatic test equipment to find the relationship between system function failure and parameter degradation. Static bias is more sensitive than dynamic bias when DSP is tested on-line during radiation. Core current, high-Z leakage current and timing parameter are sensitive to ionizing radiation. No enhanced low-dose-rate sensitivity is found by comparing experiment results under high and low dose rate radiation. External memory interface and Timer are deduced to be the sensitive module by step radiation and analysis basing full parameter test in Verigy 93000. The timing parameter degradation have a strong correlation to these module functions. And the degeneration mechanism is analysed on inverter through Hspice simulation which indicate the leakage circuit caused by radiation can lead a delay to the digital signal propagating. The parasitical capacitance among long connections make it worse to the data transmission around DSP, field programmable gate array and memory. Then an early function failure occurs in test board than Verigy 93000. This work provide support to systematic radiation hardness design and hardness assurance/lot acceptance testing in space applications.

Image sensor with a plurality of super-pixels

Abstract: The present disclosure generally relates to image sensors and methods for image sensing. More specifically, and without limitation, this disclosure relates to systems and methods for providing super-pixels, and implementing and using image sensors with super-pixels. In one implementation, an image sensor includes a plurality of super-pixels. Each super-pixel may include a first photosensitive element; a detector electrically connected to the first photosensitive element and configured to generate a trigger signal when an analog signal proportional to brightness of light impinging on the first photosensitive element matches a condition; a second photosensitive element; an exposure measurement circuit electrically connected to the second photosensitive element and configured to convert an analog signal proportional to brightness of light impinging on the second photosensitive element to a digital signal; and a logic circuit electrically connected to the detector and the exposure measurement circuit and configured to enable the exposure measurement circuit in response to the trigger signal and to disable the exposure measurement circuit when the digital signal is read out from the exposure measurement circuit.

Synchronizing phasor measurement and STATCOM controller in power system stability enhancement

Abstract: The objective of this paper is to present the concepts of synchronizing phasor measurement (SPM) and its strategic application in addition with a STATCOM controller for augmentation of dynamic stability in a multimachine power network. The bus voltages of the power network under consideration are estimated in the form of digital signal by a synchronizing phasor measurement unit (SPMU). The output of the PMU is then applied to a fixed structure PI type lead-lag digital STATCOM controller in order to study the performance of this discrete-time digital control in comparison to its analog counterpart for the present control problem. The parameters of the analog controller are first tuned with a popular soft computation technique, particle swarm optimization (PSO) and later this controller is converted to digital one for simulation with sampled data outputs received from SPMU. The validation and effectiveness of the design of the proposed control scheme is illustrated through time domain simulation of a proposed 3- machine, 9-bus test power system. The simulation results of the machine speed deviation response established that the SPM based digital control system is more effectual and resulting better performance than the continuous-time analog control system in power system stability improvement.