Signal Processing Module Research Articles

Physical secure key distribution based on chaotic self-carrier phase modulation and time-delayed shift keying of synchronized optical chaos.

High speed physical secure key distribution in a classical optical fiber channel is unprecedentedly desired for modern secure communication, but it still remains a worldwide technical challenge. In this paper, we propose and experimentally demonstrate a novel high-speed physical secure key distribution scheme based on chaotic optical signal processing and private hardware modules, which employs chaotic self-carrier phase modulation for chaotic bandwidth expansion and time-delayed shift keying of commonly driven synchronized optical chaos for physical layer security. In this scheme, the entropy source rate of synchronized chaos output from two remote response lasers is greatly expanded by chaotic self-carrier delayed nonlinear phase disturbance, which facilitates high speed key extraction from the entropy source with guaranteed randomness. Moreover, a synchronization recovery time of sub-nanosecond is achieved by dynamic keying of the chaotic delay time after chaos synchronization to accelerate the key distribution rate. Based on the proposed scheme, a high physical key distribution rate of 2.1 Gb/s over 40 km is successfully demonstrated in the experiment. The proposed solution provides a promising strategy for future high-speed key distribution based on chaotic optical signal processing and classical fiber channel.

THz-over-fiber transmission with a net rate of 5.12 Tbps in an 80 channel WDM system.

An experimental demonstration of the ultra-large-capacity terahertz (THz)-wave signal transmission over a 20-km wired and 54-m wireless distance in an 80-channel wavelength division multiplexing (WDM) system is successfully realized for the first time, to the best of our knowledge. Based on optical asymmetric single-sideband (ASSB) modulation and advanced digital signal processing (DSP) algorithms, we achieve a record line rate of 6.4 Tbit/s (net rate of 5.12 Tbit/s) in a THz-over-fiber communication system. This experimental demonstration can provide an effective solution for ultra-large-capacity THz-over-fiber communication in future 6G networks.

Intelligent Decision Support and Fusion Models for Fault Detection and Location in Power Grids

Computational intelligence-based diagnostic frameworks have emerged as rapidly evolving but highly efficient approaches for diagnosing faults in power grids. This work aims to build a diagnostic framework by resorting to computational intelligence techniques to improve decision-making and diagnostic accuracy. This diagnostic framework has three modules for signal processing, fault detection, and location. The signal-processing module uses the variational mode decomposition technique to extract informative time-frequency features from the voltage and frequency signals. Voltage features are then fed into the fault detection module to train a set of modular support vector machines that are used for monitoring the binary state of each node in the power grid. Once a faulty state on a node is detected, it activates the third module for identifying fault location. This module benefits from a novel zSlices-based general type-2 fuzzy fusion model for the sake of identifying the fault type as well as mitigating the false alarm rate. The exact location of the fault is then determined through a fuzzy decision support system that is equipped with a recommendation mechanism for the sake of consensus reaching. Various scenarios are simulated on the IEEE 39-bus system and on an experimental setup of a Three-Bus Two-Line transmission system, where the attained results verify the applicability, efficiency, and robustness of the proposed framework.

The Research and implementation of high-speed Master-slave CAN-FD composite system based on Cortex-M7

All CAN bus is widely used in communication and control between electronic control units of automobiles. At present, the rapid development of intelligent network system has put forward higher requirements on the speed, capacity, reliability and stability of real-time data exchange.In this paper, the microcontroller based on Cortex-M7 architecture and the third-generation high-speed CAN transceiver are selected to build the interface module. According to the high-level CAN communication protocol, the control command is sent and the fault diagnosis and status monitoring is carried out in real time. At the same time, the industrial data from the signal processing module is received and stored. The test results show that the interface system is configured with several groups of filters of different interception modes based on the dual-channel CAN-FD communication, realizing higher transmission rate, longer data frames and multiple frame sending and receiving and is downward compatible with BxCAN. It has the characteristics of strong comprehensive performance, high reliability, portability and versatility. It also provides theoretical verification and data support for the optimization design and application of CAN bus in domestic industrial products.

A Deep Learning-Based Intelligent Receiver for Improving the Reliability of the MIMO Wireless Communication System

Multiple-input–multiple-output (MIMO) technology is one of the most widely used communication technologies. However, with the increasing number of antennas, the complexity of the MIMO wireless communication receiver becomes higher and higher. On the other hand, the complex communication channels also raise up a great challenge to the reliability of the communication receiver system. With the rapid development and wide application of deep learning, it has been applied in the field of communication to solve some problems that are difficult to solve by the traditional methods, and thereby, improves the reliability of communication systems. Inspired by this idea, this article reviewed the signal processing process of the MIMO receiver system from the perspective of system reliability. Based on deep learning, the signal processing modules of the receiver system are jointly optimized, which changes the information recovery process of the traditional receiver and proposes the intelligent receiver for MIMO communication. In order to verify the system reliability of the intelligent receiver, this article analyzes it from the aspects of antenna numbers and channel conditions. The influence of different implementation methods of the intelligent receiver on the system reliability is also analyzed. Simulation results show that the proposed intelligent receiver for the MIMO wireless communication can recover information with a lower bit error rate and higher reliability compared with the traditional receiver under different conditions and antenna configurations.

Multiple target recognition and position identification circuit based on memristor

Traditional target recognition has low precision and the data processing is complicated when recognizing multiple targets. A multiple target recognition and position identification circuit based on memristor is designed in this paper, which can simultaneously realize the recognition for multiple targets with different shapes. The dual recognition is used in the designed recognition circuit, including position identification and size recognition, which will improve the recognition accuracy. Integral holding module and double threshold detection module with variable threshold based on memristor can flexibly construct the circuit according to different requirements, and the application range of the circuit is expanded. The signal processing module is designed in this paper to effectively filter out redundant targets and improve the reliability of the circuit. Different from the existing target recognition technologys, the multiple target recognition circuit based on memristor adopts the method of analog circuit to provide reference for the further development of target recognition.

Direct Modulation and Free-Space Transmissions of up to 6 Gbps Multilevel Signals With a 4.65-$\mu$m Quantum Cascade Laser at Room Temperature

A roadmap for future wireless communications is expected to exploit all transmission-suitable spectrum bands, from the microwave to the optical frequencies, to support orders of magnitude faster data transfer with much lower latency than the deployed solutions nowadays. The currently under-exploited mid-infrared (mid-IR) spectrum is an essential building block for such an envisioned all-spectra wireless communication paradigm. Free-space optical (FSO) communications in the mid-IR region have recently attracted great interest due to their intrinsic merits of low propagation loss and high tolerance of atmospheric perturbations. Future development of viable mid-IR FSO transceivers requires a semiconductor source to fulfill the high bandwidth, low energy consumption, and small footprint requirements. In this context, quantum cascade laser (QCL) appears as a promisingtechnological choice. In this work, we present an experimental demonstration of a mid-IR FSO link enabled by a 4.65-μm directly modulated (DM) QCL operating at room temperature. We achieve a transmission data rate of up to 6 Gbps over a 0.5-m link distance. This achievement is enabled by system-level characterization and optimization of transmitter and receiver power level and frequency response and assisted with advanced modulation and digital signal processing (DSP) techniques. This work pushes the QCL-based FSO technology one step closer to practical terrestrial applications, such as the fixed wireless access and the wireless mobile backhaul. Such a QCL-based solution offers a promising way towards the futuristic all-spectra wireless communication paradigm by potentially supporting the whole spectrum from the MIR to the terahertz (THz).

A button switch inspired duplex hydrogel sensor based on both triboelectric and piezoresistive effects for detecting dynamic and static pressure

The capability to sense complex pressure variations comprehensively is vital for wearable electronics and flexible human–machine interfaces. In this paper, inspired by button switches, a duplex tactile sensor based on the combination of triboelectric and piezoresistive effects is designed and fabricated. Because of its excellent mechanical strength and electrical stability, a double-networked ionic hydrogel is used as both the conductive electrode and elastic current regulator. In addition, micro-pyramidal patterned polydimethylsiloxane (PDMS) acts as both the friction layer and the encapsulation elastomer, thereby boosting the triboelectric output performance significantly. The duplex hydrogel sensor demonstrates comprehensive sensing ability in detecting the whole stimulation process including the dynamic and static pressures. The dynamic stress intensity (10–300 Pa), the action time, and the static variations (increase and decrease) of the pressure can be identified precisely from the dual-channel signals. Combined with a signal processing module, an intelligent visible door lamp is achieved for monitoring the entire “contact–hold–release–separation” state of the external stimulation, which shows great application potential for future smart robot e-skin and flexible electronics.

Design of Permanent Magnet Synchronous Motor Power-assisted System Based on Field Oriented Control Algorithm

Aiming at the integrated surgical robot, a set of power-assisted control system is designed to overcome the transmission resistance between master and slave hands, so that the operator feels light and comfortable during operation. The system includes permanent magnet synchronous motor, driver, controller, torque sensor, upper computer. The field oriented control algorithm is discussed and is used to control the permanent magnet synchronous motor. STM32 is used as the main control chip, DRV8301 is used as the driving chip, and the upper computer software, which has human-computer interaction interface and real-time torque signal display interface, is written by C#. A non-contact torque sensor and corresponding signal processing module is designed. The experimental results show that with the operator’s start-stop and reversing action, the q-axis current of the motor changes rapidly, and the amplitude of steady-state changes is small. This means that the designed system has the advantages of stable assist torque and fast response.

Compact and Energy-Efficient Forward-Biased PN Silicon Mach-Zehnder Modulator

A compact device model along with simulations and an experimental analysis of a forward-biased PN junction-based silicon Mach-Zehnder modulator (MZM) with a phase-shifter length of 0.5 mm is presented. By placing the PN junction to a certain off-center such that 72% of the waveguide is p-doped, the refractive index swing at a given drive voltage swing is increased by 2% compared to the symmetric layout. The effects of the phase shifters’ length mismatch and asymmetric splitting on the modulation efficiency and extinction ratio of the modulator are simulated and compared with experimental results. Without any pre-emphasis or post-processing, a high-speed operation up to 15 Gb/s using a non-return-to-zero modulation format is demonstrated. A modulation efficiency ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{\boldsymbol{V}}_{\boldsymbol{\pi}}}{\boldsymbol{L}}$</tex-math></inline-formula> ) as low as 0.07 V × cm is verified and power consumption of 0.88 mW/Gb/s is recorded while a high extinction ratio of 33 dB is experimentally demonstrated. Compared to previously reported forward-biased silicon integrated modulators, without active tuning of the power splitting ratio between the arms, the extinction ratio is 10 dB higher. This MZM along with its compact structure is also sufficiently energy-efficient due to its low power consumption. Thus, it can be suitable for applications like analog signal processing and high-order amplitude modulation transmissions.

Highly integrated watch for noninvasive continual glucose monitoring

This article reports a highly integrated watch for noninvasive continual blood glucose monitoring. The watch employs a Nafion-coated flexible electrochemical sensor patch fixed on the watchband to obtain interstitial fluid (ISF) transdermally at the wrist. This reverse iontophoresis-based extraction method eliminates the pain and inconvenience that traditional fingerstick blood tests pose in diabetic patients’ lives, making continual blood glucose monitoring practical and easy. All electronic modules, including a rechargeable power source and other modules for signal processing and wireless transmission, are integrated onto a watch face-sized printed circuit board (PCB), enabling comfortable wearing of this continual glucose monitor. Real-time blood glucose levels are displayed on the LED screen of the watch and can also be checked with the smartphone user interface. With 23 volunteers, the watch demonstrated 84.34% clinical accuracy in the Clarke error grid analysis (zones A + B). In the near future, commercial products could be developed based on this lab-made prototype to provide the public with noninvasive continual glucose monitoring.

Monitoring the Degree of Comfort of Shoes In-Motion Using Triboelectric Pressure Sensors with an Ultrawide Detection Range.

Shoes play an important role in sports and human daily life. Here, an in-shoe sensor pad (ISSP) attached to the vamp lining is based on a triboelectric nanogenerator (TENG) for monitoring the real-time stress distribution on the top side of a foot. Each sensor unit on this ISSP is an air-capsule TENG (AC-TENG) consisting of activated carbon/polyurethane (AC/PU) and microsphere array electrodes. The detection range of each AC-TENG reaches 7.27 MPa, which is enough for monitoring the pressure change during different sports. This multifunctional ISSP can realize many typical functions of conventional smart shoes, including step counting and human-machine interaction. Moreover, it can also reveal special information, including the fitness of shoes, the stress concentration on toes, and the in-motion comfort degree. The signal processing and data transmission modules in the system have a hybrid power supply with wireless power transfer, while the real-time information about feet can be observed on a cell phone. Hence, this ISSP provides a potential approach to study the feet motion and comfort degree of shoes in long-term operations, which can guide both athlete training and the customized design of shoes.

A self-powered intelligent glove for real-time human-machine gesture interaction based on piezoelectric effect of T-ZnO/PVDF film

In the emerging field of human-machine interaction, intelligent gesture recognition techniques have great application prospects. The traditional use of rigid and over-sized power units has restrained the development of wearable gesture recognition systems. Here, we present a self-powered intelligent glove based on piezoelectric motion sensor arrays for real-time gesture recognition. The system can be confortably worn on human hands, and mainly consists of three parts: a flexible piezoelectric motion sensor based on T-ZnO/PVDF film (T-ZnO, tetrapod ZnO nanostructures), a signal processing module for analyzing the sensing information, and a Bluetooth unit for wireless communication. The system can work without external power, and the piezoelectric output can act as both the energy source of the system and the sensing signal. The working mechanism can be attributed to the piezoelectric effect of T-ZnO/PVDF composites and with flexion and extension of the fingers, a series of pulse signals can be generated and converted into specific corresponding codes. The sensing signal can be wirelessly transmitted to smartphones through the Bluetooth unit, and the phone can recognize the codes corresponding to sign language actions and translate them. This work can potentially promote the development of the next generation of human-machine interaction systems and expand the scope of self-powered techniques and wearable electronics.

Nondestructive Dimension Sorting by Soft Robotic Grippers Integrated with Triboelectric Sensor.

In smart logistics, traditional manual sorting and sorting systems based on rigid manipulators limit the warehousing development and damage the goods. Here, a nondestructive sorting method based on bionic soft fingers is proposed. This method is implemented by the soft robotic gripper (SRG) for grasping of the breakable objects, the triboelectric sensor (TES) for size sorting of the objects, and the signal processing module. In the fabrication of SRG, the silicon rubber is prepared by controlling the material synthesis process, and its Young's modulus is 600.91 kPa, which is comparable to the Young's modulus of skin tissue. Also, the maximum input pressure of SRG is 71.4 kPa. The TES has a linear relationship between pulse number and sliding displacement, and its resolution is 3 mm. It induces pulse signal sequences to quantify the SRG bending state and thus realize the size sorting of objects. Additionally, a nondestructive sorting system based on TES and SRG has been developed for fruit sorting (e.g., apples, oranges), enabling nondestructive grasping and accurate sorting. Its sorting range is 70-120 mm, and the sorting accuracy rate is up to 95%. This work also provides a way for the application of SRG and triboelectric sensors in the sorting field.

Wearable humidity sensors based on bar-printed poly(ionic liquid) for real-time humidity monitoring systems

Wearable chemical sensors can provide crucial human-physiology information by monitoring humidity in various environments. Capacitive-type humidity sensors based on poly(ionic liquid) (PIL) as the sensing material, which was synthesized via the polymerization of an ionic liquid (IL) were developed. The PIL films fabricated through a facile bar-printing process in ambient air, exhibited outstanding capacitive characteristics over a broad relative humidity (RH) range of 10%−80% at frequencies between 100 Hz and 1 MHz. Notably, high sensitivity (1.8 nF/%RH), good linearity (R2 = 0.980), low hysteresis, and fast response (~20 ms) of the developed humidity sensors were achieved. The corresponding sensing mechanism of the PIL for capacitive-type humidity sensors was studied by investigating the chemisorption of water molecules on the PIL surface and proton hopping through multiple layers of water molecules physisorbed on chemisorbed water molecules through single hydrogen bonding. In addition, the operational stability of the wearable humidity sensors developed in this study was investigated by analyzing the capacitive characteristics of the PIL sensing material at various temperatures (20–60 °C), even under a bending state and after 20,000 bending-stress cycles with a strain of 30%. Finally, a real-time humidity monitoring system integrated with signal processing and wireless communication modules was demonstrated by analyzing real-time capacitive signals acquired from a wearable humidity sensor attached to a human wrist and by visualizing processed humidity information on a user’s smartphone.

Wearable Pressure Sensors Based on MXene/Tissue Papers for Wireless Human Health Monitoring.

Though the widely available, low-cost, and disposable papers have been explored in flexible paper-based pressure sensors, it is still difficult for them to simultaneously achieve ultrahigh sensitivity, low limit and broad range of detection, and high-pressure resolution. Herein, we demonstrate a novel flexible paper-based pressure sensing platform that features the MXene-coated tissue paper (MTP) sandwiched between a polyimide encapsulation layer and a printing paper with interdigital electrodes. After replacing the polyimide with weighing paper in the MTP pressure sensor, the silver interdigital electrodes can be recycled through incineration. The resulting pressure sensor with polyimide or paper encapsulation exhibits a high sensitivity of 509.5 or 344.0 kPa-1, a low limit (∼1 Pa) and a broad range (100 kPa) of detection, and outstanding stability over 10 000 loading/unloading cycles. With ultrahigh sensitivity over a wide pressure range, the flexible pressure sensor can monitor various physiological signals and human movements. Configuring the pressure sensors into an array layout results in a smart artificial electronic skin to recognize the spatial pressure distribution. The flexible pressure sensor can also be integrated with signal processing and wireless communication modules on a face mask as a remote respiration monitoring system to wirelessly detect various respiration conditions and respiratory abnormalities for early self-identification of opioid overdose, pulmonary fibrosis, and other cardiopulmonary diseases.

Nondestructive Detection of Ceramic Products Based on Tapping Sound Signal Feature Recogition

Recent studies on the test of ceramic non-destructive testing are mainly based on high cost technologies, image processing and so on, these method possesses some drawback of low efficiency, high cost and so on. What’s more, detecting whether the ceramic products by human through listening to sound of tapping is also effectless. This paper proposed a non-destructive method for ceramic products to solve this problem. This non-destructive method consists of a tapping device and a signal processing module. The tapping device will be applied to generate the tapping sound signal and the signal processing system will be applied to analysis signal. After the process of signal analysis, sample length and peak of spectrum 2 parameters is extracted, then use these parameters to train SVM, the results will be compared with BP neural network (BPNN). The result of experiment shows that SVM with different kernels of linear, poly, rbf, sigmoid respectively reach the accuracy of 96.29%, 96.29%, 46.29%, 93.82%, while BPNN reaches the accuracy of 93.21%. This result proves that SVM can effectively complete the task of identifying defective ceramics, and its performance is better than BPNN.

Towards Explainable Augmented Intelligence (AI) for Crack Characterization

Crack characterization is one of the central tasks of NDT&amp;E (the Non-destructive Testing and Evaluation) of industrial components and structures. These days data necessary for carrying out this task are often collected using ultrasonic phased arrays. Many ultrasonic phased array inspections are automated but interpretation of the data they produce is not. This paper offers an approach to designing an explainable AI (Augmented Intelligence) to meet this challenge. It describes a C code called AutoNDE, which comprises a signal-processing module based on a modified total focusing method that creates a sequence of two-dimensional images of an evaluated specimen; an image-processing module, which filters and enhances these images; and an explainable AI module—a decision tree, which selects images of possible cracks, groups those of them that appear to represent the same crack and produces for each group a possible inspection report for perusal by a human inspector. AutoNDE has been trained on 16 datasets collected in a laboratory by imaging steel specimens with large smooth planar notches, both embedded and surface-breaking. It has been tested on two other similar datasets. The paper presents results of this training and testing and describes in detail an approach to dealing with the main source of error in ultrasonic data—undulations in the specimens’ surfaces.

Lightweight and irreversible speech pseudonymization based on data-driven optimization of cascaded voice modification modules

In this paper, we propose a speech pseudonymization framework that utilizes cascaded and superposition-based voice modification modules. With increasing opportunities to use spoken dialogue systems nowadays, research regarding protecting the privacy of speaker information encapsulated in speech data is attracting attention. Pseudonymization, which is one method for voice privacy protection, aims to keep the intelligibility of speech while simultaneously suppressing speaker-specific information. One motivation of our framework is to achieve a reliable pseudonymization performance with light computation. To do this, we utilize the advantages of both machine learning-based and signal processing-based approaches. The advantages are (1) using signal processing-based methods parameterized with few hyperparameters and (2) using machine learning-based optimization to optimize all hyperparameters on the basis of black-box systems consisting of automatic speaker verification and automatic speech recognition. Our method of cascading signal processing modules, which are jointly optimized in a data-driven manner, can pseudonymize speech in a lightweight manner. Additionally, we discuss irreversible pseudonymization approaches and propose a superposition approach, yet another pseudonymization method that is more irreversible than the cascade method in terms of estimating the adequate parameters to recover the original signal. From the experimental results conducted under the VoicePrivacy 2020 protocols, we can demonstrate that (1) our cascade method succeeds in deteriorating the speaker recognition rate by over 24% while simultaneously improving the speech recognition rate by approximately 8% compared with a signal processing-based baseline system of VoicePrivacy 2020 and that (2) our superposition method works comparable to our cascade method in terms of pseudonymization performance.

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

Joint communication and radar sensing (JCR) represents an emerging research field aiming to integrate the above two functionalities into a single system, sharing a majority of hardware and signal processing modules and, in a typical case, sharing a single transmitted signal. It is recognised as a key approach in significantly improving spectrum efficiency, reducing device size, cost and power consumption, and improving performance thanks to potential close cooperation of the two functions. Advanced signal processing techniques are critical for making the integration efficient, from transmission signal design to receiver processing. This paper provides a comprehensive overview of JCR systems from the signal processing perspective, with a focus on state-of-the-art. A balanced coverage on both transmitter and receiver is provided for three types of JCR systems, communication-centric, radar-centric, and joint design and optimization.