Digital Signal Processing Technology Research Articles

Thin-film lithium niobate-based electro-optic comb cloning for self-homodyne coherent communication.

As the optical communication industry advances, metropolitan area networks (MANs) and radio access networks (RANs) are extensively deployed on a large scale, demanding energy-efficient integrated light sources and simplified digital signal processing (DSP) technologies. The emergence of thin-film lithium niobate (TFLN) has given rise to high-performance, energy-efficient on-chip modulators, making on-chip optical frequency comb (OFC) more appealing. Owing to the phase uniformity and stability of this chip-scale device, it has been possible to eliminate the carrier frequency phase estimation (CPE) in DSP stacks using comb-clone-enabled self-homodyne detection. Here we report the first use, to our knowledge, of a TFLN on-chip electro-optic (EO) frequency comb to realize comb cloning and self-homodyne coherent detection. We transmit three optical pilot tones and eight data channels encoded with 20 Gbaud polarization-multiplexed 16-ary quadrature amplitude modulation (PM-16-QAM) over 10 km and 80 km standard single-mode fibers. The bit error ratios (BERs) of the eight channels reach below 10-3, a result made possible by our on-chip comb. The scalability and mass producibility of on-chip EO combs, combined with the simplified DSP, show potential in our proposed fifth-generation (5G) RAN and MAN transmission scheme.

Enhancing Electric Vehicle Charger Performance with Synchronous Boost and Model Predictive Control for Vehicle-to-Grid Integration

This paper investigates optimizing the power exchange between electric vehicles (EVs) and the grid, with a specific focus on the DC-DC converters utilized in vehicle-to-grid (V2G) systems. It specifically explores using model predictive control (MPC) in synchronous boost converters to enhance efficiency and performance. Through experiments and simulations, this paper shows that replacing diodes with SIC MOSFETs in boost converters significantly improves efficiency, particularly in synchronous mode, by minimizing the deadtime of SIC MOSFETs during switching. Additionally, this study evaluates MPC’s effectiveness in controlling boost converters, highlighting its advantages over traditional control methods. Real-world validations further validate the robustness and applicability of MPC in V2G systems. This study utilizes TMS320F28379D, one of Texas Instruments’ leading digital signal processors, enabling the implementation of MPC with a high PWM frequency of up to 200 MHz. This processor features dual 32-bit CPUs and a 16-bit ADC, allowing for high-resolution readings from sensors. Leveraging digital signal processing technologies and advanced electronic circuits, this study advances the development of high-performance boost converters, achieving power outputs of up to 48 watts and output voltages of 24 volts. Electronic circuits (PCB boards) have been devised, implemented, and evaluated to showcase their significance in advancing efficient V2G integration.

Mitigating the Strong Inter-Core Crosstalk during MCF Transmissions by Neural-Network-Equalizer-Based MIMO-DSP and Approaches for Its Simplification

In this paper, we report our recent progress related to advanced digital signal processing (DSP) technologies to address the strong inter-core crosstalk (IC-XT) during multicore fiber (MCF) optical transmissions. MCF transmission technology has significant potential to break through the capacity crunch of single-mode fiber (SMF) transmissions. However, strong coupling among cores, namely, inter-core crosstalk (IC-XT), is unavoidable for high-density space-division multiplexing (SDM) transmissions using MCFs with the standard cladding size. To deal with this issue, we propose some novel DSP structures to eliminate IC-XT with considerable simplicity, based on the neural network equalizer (NNE)-based multiple-input and multiple-output digital signal processing (MIMO-DSP). The traditional NNE-based MIMO-DSP method has the ability to process the coupled SDM tributaries transmitted over MCFs; however, it exhibits complexity limitations for practical implementations. The implementation complexity of the NNE-based method is mainly attributed to the time-consumption of the training process and the large weight (neurons) numbers of the equalizers. Thus, we propose two main approaches to simplify NNE-based MIMO-DSP for the practical implementation of MCF transmissions: (1) To reduce the time-consumption of the training process in NNE-based MIMO-DSP, the idea of transfer learning (TL) is employed for initializing the weights, resulting in the faster convergence of the equalizers. (2) IC-XT cancellation is performed along with MIMO-DSP; thus, the dimensionality of MIMO-DSP could be reduced. To validate the performance improvement of the proposed machine learning DSP methods, both simulations and experiments related to transmissions and reception over MCFs were conducted. The results indicate that the proposed novel DSP structures possess the advantages of reduced complexity and improved robustness to IC-XT, which is beneficial for the next-generation high-density SDM transmissions.

Revolutionizing Digital Signal Filters: A Breakthrough in Low-Power Multipliers

In the ever-evolving landscape of digital signal processing technology, the ubiquitous presence of digital signal filters has become a cornerstone across a myriad of domains including radar, computing, and communications. Amidst the relentless pursuit of more efficient solutions, a pivotal development emerges - the creation of a low-power multiplier tailored explicitly for digital signal filters. This innovation hinges upon the judicious selection of a carry-lookahead adder as a fundamental building block within the multiplier, ushering in enhancements that ripple through its operation. This transformative leap doesn't halt at the component level; it extends its reach further by delving into meticulous optimizations encompassing logic gate dimensions and set voltage parameters. These refinements, executed with precision, culminate in a substantial reduction in the energy consumption of the multiplier, effectively setting it apart from conventional counterparts. Remarkably, these advances don't merely remain theoretical; they find their footing in practical industry applications, thus birthing a new era in the creation of low-power digital signal filters. The profound implications of this development reverberate far and wide, notably benefiting the realm of low-power digital signal processing and its associated applications.

Recent Advances in Low-Power Digital Signal Processing Technologies for Data Center Applications

Recent Advances in Low-Power Digital Signal Processing Technologies for Data Center Applications

Trade-offs Between Delay and Energy in 4-Bit Absolute Value Detector and its application analysis

With the rapid advancements in digital signal processing and communication technology, the utilization of digital detectors has become prevalent across numerous domains. Among these detectors, absolute value detectors hold particular significance. This article primarily delves into the delicate balance between latency and energy consumption within the realm of 4-bit absolute value detectors. To commence, we provide an exhaustive exposition of the fundamental design and operational principles underpinning absolute value detectors. Subsequently, we embark on a comprehensive comparison of various optimization approaches, with a special focus on their efficacy concerning energy consumption and latency. The research endeavors have unveiled that the detector's optimal aspect ratio, as well as the choice of novel materials like graphene and silicon germanium, can wield a substantial influence over its performance. As its peer into the horizon, it is evident that the continuous evolution of new materials and cutting-edge technologies promises further enhancements in the performance of 4-bit absolute value detectors.

Design and implementation of 4-bit absolute value detector based on verilog HDL

Absolute value detectors are widely utilized in many disciplines, such as image processing, speech recognition, and control systems, due to the advancement of digital signal processing and computer vision technologies. This paper presents a 4-bit absolute value detector based on the Verilog HDL programming language. Absolute value detectors are extensively used in signal processing, computer vision, and other fields to determine if the absolute value of the input signal meets specific conditions. This paper describes in detail the design process, including module analysis, the drawing of state transfer diagrams, the writing of Verilog HDL code, and simulation verification with a focus on practical applications. The results demonstrate that the absolute value detector is accurate and reliable in determining whether the absolute value of the input signal is greater than or equal to the threshold value.

Analysis and application of key technologies in digital signal processing

With the uncreasing reform of times and the continuous advancement of my science and technology, in recent years, my overall national strength is strengthening gradually. I have entered an information age, one digital age, the use of digital signal processing is becoming more and more frequent and important. Therefore, this paper mainly analyzes the application of DSP, the digital signal processing technology show to make the exposition. Digitalization is a major trend in today's society and the main theme of the development of the times, while digital signal processor is a component born with the times. The so-called digital signal processing is to use a universal digital signal chip to extract useful information from the signal by digital calculation. In recent years, in the wake of the constantly improving of science and technology and the continuous reform and innovation of technology in China, DSP is more and more close to people's production and life, and plays an important role in practical applications. Therefore, it is necessary to discuss and analyze its development.

Key Technologies for a Beyond-100G Next-Generation Passive Optical Network

The explosive development of emerging telecommunication services has stimulated a huge growth in bandwidth demand as people seek universal access to telecommunication networks. In addition, the kinds of services of an existing optical access network are becoming more flexible. In order to provide higher capacity and meet higher transmission performance requirements, it is necessary to further explore the application of the beyond-100G passive optical network (PON). This paper offers a comprehensive review and outline of the prospects of technologies for bringing a beyond-100G PON to practical applications in the future. We review the current existing technologies, mainly in terms of the physical layer and higher media access control layer. These key technologies for the beyond-100G PON, which plays an increasingly significant role, include the advanced multiplexing technology, physical layer digital signal processing technology, infrastructure-sharing technology, security protection technology, and intelligent control management key technologies. Finally, open issues and new challenges for the next-generation PON are focused upon.

An absolute ranging method based on FMCW principle using dual laser interferometry

The FMCW (Frequency Modulated Continuous Wave) laser interferometer can achieve high-precision displacement measurement by calculating the phase of the interference signal. Due to the need for continuous superposition of signal phases, the optical path and power supply cannot be interrupted during the measurement process. To solve this problem, this article proposes a new absolute ranging method—the decimal comparison method. Two distributed feedback lasers with different central wavelengths are used to measure the same target. The digital signal processing technology is used to solve the sampled interference signals, and the initial phase value corresponding to the decimal of interference is taken. Combined with the central wavelength of the two laser sources, the length variation of the F–P cavity corresponding to the number of interference periods is calculated. Finally, the optical path difference of the target is calculated by the established mathematical model. The experimental results show that this method can realize the absolute measurement of laser interferometry and can expand the application range of FMCW interferometry.

Design of A High-Precision Component-Type Vertical Pendulum Tiltmeter Based on FPGA.

This paper presents a high-precision component-type vertical pendulum tiltmeter based on an FPGA (Field Programmable Gate Array) that improves the utility and reliability of geophysical field tilt observation instruments. The system is designed for rapid deployment and offers flexible and efficient adaptability. It comprises a pendulum body, a triangular platform, a locking motor and sealing cover, a ratiometric measurement bridge, a high-speed ADC, and an FPGA embedded system. The pendulum body is a plumb-bob-type single-suspension wire vertical pendulum capable of measuring ground tilt in two orthogonal directions simultaneously. It is installed on a triangular platform, sealed as a whole, and equipped with a locking motor to withstand a free-fall impact of 2 m. The system utilizes a differential capacitance ratio bridge in the measurement circuit, replacing analog circuits with high-speed AD sampling and FPGA digital signal processing technology. This approach reduces hardware expenses and interferences from active devices. The system also features online compilation functionality for flexible measurement parameter settings, high reliability, ease of use, and rapid deployment without the need for professional technical personnel. The proposed tiltmeter holds significant importance for further research in geophysics.

Continuous-mode quantum key distribution with digital signal processing

Continuous-variable quantum key distribution (CVQKD) offers the specific advantage of sharing keys remotely by the use of standard telecom components, thereby promoting cost-effective and high-performance metropolitan applications. Nevertheless, the introduction of high-rate spectrum broadening has pushed CVQKD from a single-mode to a continuous-mode region, resulting in the adoption of modern digital signal processing (DSP) technologies to recover quadrature information from continuous-mode quantum states. However, the security proof of DSP involving multi-point processing is a missing step. Here, we propose a generalized method of analyzing continuous-mode state processing by linear DSP via temporal modes theory. The construction of temporal modes is key in reducing the security proof to single-mode scenarios. The proposed practicality oriented security analysis method paves the way for building classical compatible digital CVQKD.

Research on Pulse Shaper Based on Trapezoidal Function

In order to improve the time resolution and spatial resolution of photon-counting imaging system, the pulse shaper based on trapezoidal function is studied. The signal with an exponential decay shape from charge sensitive amplifier is converted to digital discrete signal by ADC and then the discrete number sequence is filtered and shaped by digital signal processing technology. The amplitude linearity and time width of the trapezoidal shaper are simulated and verified using software-generated single exponential signals and double exponential signals. While the continuous pulses are applied to the trapezoidal shaper, the separation characteristics of the trapezoidal algorithm for pulses pile-up is verified, and the setting method of the rise edge and fall edge parameters of the trapezoidal shaper is proposed, which can realize the high counting capability of the system.

Artificial Intelligence-based Musical Instrument Accompaniment System

The string learning process requires students to be able to accurately grasp the accuracy of notes and rhythms in the process of playing, and its evaluation is usually done by instructors, but long one-on-one instruction is difficult to achieve in actual teaching. In this project, through the research of audio hardware systems and digital signal processing software technology, I design a string performance recognition robot system combining hardware and software, to realize automatic accompanying practice. The hardware of this system consists of a Raspberry Pi card-type computer, recording equipment, and cueing equipment. The software system processes the audio signal collected by the microphone through artificial intelligence technology and digital signal processing technology to realize the recognition of notes, intensity, and other elements according to the frequency characteristics of string instruments. The accuracy of the user's performance is judged by comparing the recognition result with the content of the score, and the user is guided by real-time hints through the display system. The experimental results show that the system can recognize 99% of the string audio with good recognition stability, so it can give accurate and timely performance guidance to the player.

Experimental studies on compaction of soil with HAMM 3411 vibrating roller

Introduction. Mathematical modelling is used to assess the influence of various factors on the result of soil compaction by a vibratory roller. The verification of the mathematical model is carried out by comparing it with the results of the experimental studies. Expanding the list of the roller models in the experimental studies allows expanding the range of conditions for verification of the mathematical model. The article presents the results of field experimental studies of soil compaction by HAMM 3411 vibrating roller. The data on the change in the value of the dynamic soil deformation modulus Evd depending on the number of passes of the roller during compaction of sandgravel mixture with a layer thickness of 0.5 m have been obtained. The peculiarities that are reasonable to take into account when carrying out further experimental research are revealed.Materials and methods. The experimental studies of the scope of vertical movements of the roller, as well as vertical accelerations of the roller and its frame were carried out on a HAMM 3411 vibrating roller during compaction of a sand-gravel mixture. The result of compaction of the soil after each pass was estimated by the value of the dynamic deformation modulus Evd, measured using the ZORN ZFG 3.0 dynamic loading unit. In the experiment, vertical movements of the vibrating roller were recorded using a BAUMER OADM 13U6480/S35A laser sensor. Accelerations of vibrations of the vibrating roller and the roller frame were recorded by piezoelectric accelerometers of the AR2099-100 and AR99-100 models. When processing sensor readings, digital signal processing technology was used – low-pass filters with a limit frequency of 200 Hz.Results. The studies were carried out on two sites with different soil moisture. On a site with waterlogged soil in the range of Evd values = 10 ...13 MPa, the amplitude values of the vertical accelerations of the roller were in the range from +20 ... +45 to -25 ...-43 m/s2, and the frames in the range from +2.5 ...+5 to -2 ...-5 m/s2. The range of vibrations of the vibrating roller in the area with waterlogged soil was 3.3...4.8 mm. On a site with soil with close to optimal importance, in the range of values Evd= 18...28 MPa, the amplitude values of vertical accelerations of the roller were in the range from +36 ... +48 to -35 ... -40 m/s2, and frames in the range from +3.5 ... +6 to -2...-4.5 m/s2.Discussion and conclusion. The results show that the range of oscillations of the drum, as well as the amplitude values of vertical accelerations of the drum and the drum frame slightly increase with increasing soil deformation modulus Evd. The results of the experiment correlate with the studies conducted on the models of rollers DM-DM-617. When measuring values of Evd in one cross-section, the difference between measured values along the axis of roller’s movement and on the pneumatic wheel track reached 30%. When analyzing obtained results, it is necessary to take into account that in the experiment the actual frequency of oscillation of the roller was 18 Hz, instead of 27 Hz as stated in the technical specifications. With such reduction of frequency, the forced force of oscillations will decrease approximately 2.25 times. Results of the experiment will help in further verification of mathematical model of the roller and in carrying out experimental researches of similar character.

Heterogenous ensemble learning driven multi-parametric assessment model for hardware Trojan detection

Semiconductor technologies have gained wide-spread attention across industries due to its use in varied digital signal processing units, healthcare-devices, industrial communication, science and technologies, entertainment, smart devices etc. However, high design-complexities, untrusted foundries, third-party processors etc., have raised the concern of intrusion, particularly Hardware Trojans. Hardware Trojan, a specifically designed micro-intruder that can cause data breaches, system malfunctions etc. And hence may result disastrous consequences. To alleviate such problems, though different methods have been suggested for Trojan detection; however, pre-manufacturing methods can't guarantee Trojan-free design due to non-trusted Foundries and Third-party IPs. Similarly, post-manufacturing methods like side channel analysis or gate -level netlist are limited due to highly complex design, large structure and unavailability of universal golden design structures. Considering it as motivation, this paper proposes a robust register transfer logic (RTL) analysis assisted multi-parameter-based machine learning-driven Hardware Trojan detection system. We applied delay, power consumption and resource utilization profiles to perform Trojan detection over AES-256 circuits. Aforesaid features were extracted using VIVADO tool, which were further employed for resampling process using SMOTE, SMOTE-ENN, SMOTE-Borderline algorithms. Here, the use of resampling intended to alleviate data-imbalance or skewness. Moreover, it helped retaining sufficiently large features for machine learning based training. The resampled features were processed for feature selection using Significant Predictor Test, Cross-Correlation Test and Principal Component Analysis (PCA), distinctly. The selected features were trained using a novel heterogenous ensemble learning model encompassing a total of 11 base-classifiers belonging to Naïve Bayes, Neuro-computing, Decision Tree, Random Forest, Extra Tree classifier and Bagging-AdaBoost algorithms. Applying the maximum voting ensemble, the proposed model performed path-level Trojan detection, where the simulated results affirmed accuracy, F-Measure and Area Under Curve (AUC) of almost 100%, which is higher than any known approaches towards Hardware Trojan detection.

Signal acquisition analyzer based on MSP432

The system is based on digital signal processing technology, takes MSP432P401R single-chip microcomputer as the main controller, uses the on-board ADC to convert the input signal into a digital signal, and then carries out FFT transformation to obtain the amplitude of each harmonic component, so as to carry out spectrum analysis and calculate THD/ THDo/ Δ values for further signal processing. The system realizes the signal processing and the calculation of distortion and distortion measurement error and expands the functions of calculating the normalized amplitude of the fundamental wave and harmonic and recovering the input signal waveform. Distortion measurement error value Δ ≤3%, can process signal amplitude range 30mV~600mV, fundamental frequency range 1kHz~100kHz, and the calculation and processing time is less than 10 seconds.

Indoor Human Fall Detection Algorithm Based on Wireless Sensing

As the main health threat to the elderly living alone and performing indoor activities, falls have attracted great attention from institutions and society. Currently, fall detection systems are mainly based on wear sensors, environmental sensors, and computer vision, which need to be worn or require complex equipment construction. However, they have limitations and will interfere with the daily life of the elderly. On the basis of the indoor propagation theory of wireless signals, this paper proposes a conceptual verification module using Wi-Fi signals to identify human fall behavior. The module can detect falls without invading privacy and affecting human comfort and has the advantages of noninvasive, robustness, universality, and low price. The module combines digital signal processing technology and machine learning technology. This paper analyzes and processes the channel state information (CSI) data of wireless signals, and the local outlier factor algorithm is used to find the abnormal CSI sequence. The support vector machine and extreme gradient boosting algorithms are used for classification, recognition, and comparative research. Experimental results show that the average accuracy of fall detection based on wireless sensing is more than 90%. This work has important social significance in ensuring the safety of the elderly.

Study on processing synthetic aperture radar data based on an optical 4f system for fast imaging.

Due to the huge amount of collected echo data caused by the working principle of synthetic aperture radar (SAR), the use of digital processing relies heavily on the performance of digital chips. Because of the limitation of Moore's law, the technology of digital signal processing exposes the limitation of computing speed and power consumption in the face of SAR processing. Against this background, the optical processing method based on the optical 4f system is introduced into SAR imaging. A spatial light modulator (SLM) is placed on the input surface and spectrum surface of the 4f system to load the echo data of the SAR and the matched filter function of the SAR. Using optical Fourier transform to realize the core calculation of SAR data processing can solve the difficulty of processing time-consuming due to the large amount of calculation. In the process of Fourier transform, instead of using a solid glass lens, we use a phase-type Fresnel lens diagram in the SLM to realize the function of Fourier, which avoids the need for special design of Fourier lens. It also greatly reduces the volume and weight of the whole machine, which provides a reference method for real-time imaging of spaceborne SAR.

Overview of high-speed TDM-PON beyond 50 Gbps per wavelength using digital signal processing [Invited Tutorial

The recent evolution of passive optical network standards and related research activities for physical layer solutions that achieve bit rates well above 10 Gbps per wavelength ( λ ) is discussed. We show that the advancement toward 50, 100, and 200 G b p s / λ will certainly require a strong introduction of advanced digital signal processing (DSP) technologies for linear, and maybe nonlinear, equalization and for forward error correction. We start by reviewing in detail the current standardization activities in the International Telecommunication Union and the Institute of Electrical and Electronics Engineers, and then we present a comparison of the DSP approaches for traditional direct detection solutions and for future coherent detection approaches.