Signal Communication Systems Research Articles

Design and optimisation of a two-stage amplifier based on a differential input stage and a common-source amplifier

Abstract. Since the emergence of integrated circuits, through the circuit structure, the production process of continuous iterative updating, so that its used in various types of electronic equipment more and more widely. Currently, operational amplifier circuits play an extremely important role in signal processing and communication systems. Amplifiers have different characteristics depending on the needs of different electronic devices. This thesis addresses the optimisation and design of the characteristics of the two-stages amplifier. Firstly, several classical amplifier structures are analysed. Select the appropriate structure and combine it into a two-stages amplifier. Simulation is carried out on cadence software and later the simulation results are analysed before parameter optimisation. On this basis, a two-stages amplifier based on a PMOS differential input stage with a common-source amplifier has been designed. It also improves the amplifier's gain, frequency range, gain bandwidth, and other performance metrics. Using PMOS self-bias circuit to improve power supply stability. Finally, based on the development hotspots of integrated circuits, the possibility of circuit optimization was analyzed. Discussions were conducted on negative feedback circuits, phase compensation methods, and other aspects.

Genetic algorithm optimized microstructure to enhance waveguide light coupling efficiency at normal incidences

The recent trend to place well-designed photonic structures on waveguides is capable of effectively enhancing waveguides properties. One typical example is a nanostructure-empowered waveguide targeted for efficient light coupling. However, conceiving the high-freedom structures is a time-consuming and labor-intensive process, where an ineffective workflow limits the development of photonic microstructures. To address this issue, we deploy a genetic algorithm to customize structures in order to improve the coupling coefficients under predetermined situations (i.e., normal incidence combined with two polarizations). Three types of micropatterns are first conceived in the periodical model and then fully characterized on the real waveguide sizes. The simulated data reveal that the 550–1650 nm average coupling efficiencies of structure-enabled waveguides are raised by about 2% in contrast to the bare case, and the lineshapes are also flattened thanks to the grating modifications. In short, our solution underlines the role of an algorithm-developed nanostructure to lift waveguide coupling coefficients. By integrating well-engineering patterns, the waveguide-based probes may find a multitude of usages for weak signal detection and communication systems.

Automatic classification of multi-carrier modulation signal using STFT spectrogram and deep CNN

In the realm of communication systems, categorizing Multi-Carrier Modulation (MCM) signals without cooperative communication poses a significant technical challenge. In this paper, we introduce a novel approach for accurately categorizing five distinct MCM signals, including Orthogonal Frequency Division Multiplexing (OFDM), Filter Bank Multicarrier (FBMC), Filtered Orthogonal Frequency Division Multiplexing (FOFDM), Windowed Orthogonal Frequency Division Multiplexing (WOLA), and Universal Filtered Multicarrier (UFMC). Each signal is considered with two types of subcarrier waveforms, Quadrature Amplitude Modulation 16 (QAM16) and Quadrature Amplitude Modulation 64 (QAM64), resulting in a total of 10 unique MCM signals for classification. Our proposed methodology leverages Short-Time Fourier Transform (STFT) spectrograms for feature extraction at the frontend, while at the backend, we employ three variants of Convolutional Neural Network (CNN) models; CNN, CNN with Dropout (CNN_d), CNN with both Dropout and L1 Regularization (CNN_dL1) and one deep CNN model; Xception, individually. We aim to provide an efficient and reliable means of categorizing MCM signals, with practical applications in signal processing and communication systems. Extensive simulations demonstrate the effectiveness of our approach, achieving remarkable accuracies. Notably, the Xception model exhibits the highest accuracy among the four models considered. Specifically, we attain an accuracy of 98% at 10 dB SNR using the Xception model. These results underscore the efficacy of our proposed methodology and highlight the potential for its deployment in real-world scenarios.

Isomerism-enabling low-temperature ultrasensitive and moisture-resistant fire-alarming “Guarder” via color changing

Aiming to integrate a low-temperature, ultrasensitive and wireless remote-monitoring fire alarming with a fire suppression into a commercialized system, in view of a heat-induced tailored isomerization of Salen molecules and sunflower configuration for a heat capturing, we constructed a quasi-core-shell MAPP@Salen with silaned ammonia polyphosphate guiding a vertical deposition of Salen lamellas assembly. Resultantly, MAPP@Salen demonstrated an ultralow triggering temperature of 120 °C and 1 s time at 250 oC with a remarkable color from yellow to dark red. A Salen isomerization and its vertical alignment on MAPP accounted for an ultra-sensitiveness feature. A model acrylic coating with MAPP@Salen presented a 0.3 s responsive time at 250 °C as well as instant (0.5 s) and unstopped warning once flame approached. A wireless signal communication system via a color recognition algorithm and 4 G IoT was realized. Additionally, the coating provided >10 min and ultrastrong intumescent fire protection via a Salen-participative charring optimization as well as well-persevered structural integrity after a long-term water attack. The fire-alarming capability was retained as well. This work pertaining to a bio-inspired hierarchical assembly integrates a low-temperature ultra-sensitive fire alarming and an optimized fire resistance for commercial all-time-scale fire retardants in multi-scenario universal applications.

Design Wallace Tree Multiplier Using Reversible Gates

Abstract: Multipliers are essential components in digital circuit design. They have wide spread applications in digital signal processing and communication systems. Circuit designers in VLSI design seek compact, small scale circuits with low power consumption and minimal delay. The Wallace tree multiplier is an advanced version of tree based multipliers. Numerous algorithms have been developed to create the fastest multipliers, and the Wallace tree multiplier is one such example. It utilizes reversible compressors, full adders, and half adders. The results demonstrate that the Wallace tree multiplier using reversible gates outperforms traditional multipliers in terms of power dissipation and delay, with values of 0.027W and 29.327nS re­spectively.

Investigation of Characteristics of Ultraviolet Light Pulse Weak Signal Communication System Based on Fourth-Order Frequency-Shift Keying Modulation

In ultraviolet (UV) communication, On–Off Keying (OOK) is the primary modulation technique. Compared to OOK, frequency modulation offers stronger resistance to path attenuation. Currently, research on frequency modulation demodulation schemes for UV communication is limited, mainly employing waveform detection and laser pulse response methods, which require high detection sensitivity to light. This study presents a novel frequency modulation communication scheme using discrete Poisson channel distribution and optical pulse signal processing algorithms, enhancing the signal processing sensitivity of the existing frequency modulation scheme to the level of photons. The proposed system model is rigorously evaluated through theoretical derivations and simulations. Additionally, a hardware system integrating optical pulse counting, frequency detection, and clock data recovery algorithms is developed. Experimental results show the system achieving a 5 kbps transmission rate under frequency modulation. In non-line-of-sight (NLOS) scenarios, communication reaches up to 65 m, with the receiver elevation angle ranging from 10° to 25° and the bit error rate (BER) stabilized at 10−4, while in line-of-sight (LOS) situations, the BER remains at 10−5 up to 400 m and 10−4 up to 700 m, achieving the farthest distance and fastest communication rate achievable in the current FSK modulation scheme of ultraviolet communication systems. The integrated components enhance its applicability in communication systems. This study offers a valuable addition to UV communication technology.

Fault Classification and Diagnosis Approach Using FFT-CNN for FPGA-Based CORDIC Processor

Within the realm of digital signal processing and communication systems, FPGA-based CORDIC (Coordinate Rotation Digital Computer) processors play pivotal roles, applied in trigonometric calculations and vector operations. However, soft errors have become one of the major threats in high-reliability FPGA-based applications, potentially degrading performance and causing system failures. This paper proposes a fault classification and diagnosis method for FPGA-based CORDIC processors, leveraging Fast Fourier Transform (FFT) and Convolutional Neural Networks (CNNs). The approach involves constructing fault classification datasets, optimizing features extraction through FFT to shorten the time of diagnosis and improve the diagnostic accuracy, and employing CNNs for training and testing of faults diagnosis. Different CNN architectures are tested to explore and construct the optimal fault classifier. Experimental results encompassing simulation and implementation demonstrate the improved accuracy and efficiency in fault classification and diagnosis. The proposed method provides fault prediction with an accuracy of more than 98.6% and holds the potential to enhance the reliability and performance of FPGA-based CORDIC circuit systems, surpassing traditional fault diagnosis methods such as Sum of Square (SoS).

Generation of high-order focused acoustic vortices and multiplexed beams using Dual-Channel metamaterials

Focused vortex beams have attracted considerable research attention due to their unique acoustic properties, and have been explored in medical imaging, biomedical therapy, and particle manipulation. Here, an acoustic metamaterial vortex generator (AMVG) is designed to realize a multiplexed focusing acoustic vortex (MFAV) with multiple-order topological charges (TCs). The proposed AMVG is composed of several fanlike sectors with two high transmission channels per unit, which can flexibly modulate the transmitted phase shift in two separate frequency bands. In contrast to conventional acoustic metamaterial-based vortices, the design strategy provides a new degree of freedom, i.e., frequency, that may extend to the agile tailoring of multi-band independent vortices, significantly enhancing the information encoded in the acoustic metamaterial. Acoustic transmission and phase shift of the dual-channel unit are investigated theoretically and demonstrated in simulations using the finite element method. The focal position and TC of the MFAVs can be modulated by simply adjusting the cavity length of the unit cell and even only the sector order. Furthermore, we implement three-dimensional anechoic experiments to verify the effectiveness of the off-axial MFAVs by the designed AMVG. These multiplexed focusing vortices offer a technical advance to tackle the rising challenges in the fields of acoustic signal processing and communication systems.

A novel integrated signal structure of satellite navigation and communication system with plug-and-play capability

An integrated navigation/communication signal is proposed in our previous work. It considered Cyclic Code Shift Keying (CCSK) as a communication signal combined with traditional Global Navigation Satellite System (GNSS) signal, further the optimized cyclic shift set for communication signal was designed. Based on the previous research, a fuzzy judging algorithm is proposed to acquire the integrated signal in this paper. This algorithm adopts segmenting correlation domain to improve the integrated signal transmission robustness. Moreover, in order to solve incompatibility problem between the integrated signal and binary communication system, a strategy for optimizing cyclic shift set basing on dual-thresholds is proposed, in which interleaving coding is used to resist interference. The fault-tolerant rate of proposed algorithm is improved by about 87% compared with traditional algorithms. Based on the compatibility, the Bit Error Rate (BER) of the integrated signal decreases obviously, and the reliability of the communication system is improved greatly, benefiting from that interleaving technology and error correction coding is applied.

An Integrated Pump-Controlled Variable Coupler Fabricated by Ultrafast Laser Writing.

The design and fabrication of a integrated symmetric directional coupler dependent o the pumping power and operating at a 1534 nm wavelength is reported. The twin-core waveguide was inscribed into Er3+/Yb3+ co-doped phosphate glass by a femtosecond laser direct writing technique. By optical pumping, the coupling ratio can be modulated due to the changes induced in the refractive index of the material. The experimental results demonstrated that the coupling ratio can be tuned continuously from 100/0 to 50/50 by increasing the pump's power from 0 to 350 mW. The developed twin-core coupler has promising applications for on-chip all-optical signal processing and communication systems.

Literature Review of Low Pass Filters Based on CMOS for Biomedical Applications

Abstract: A survey of low pass filters with good linearity, low weight, and low power consumption has been done in this study .we examine the numerous low pass filter types ,their uses and design factors in this survey. we start by looking at low pass filters fundamental concepts and characteristics of their frequency response. in this study ,many low pass filter types and associated technologies are discussed. Low pass filter with low noise ,low power requirements, and low weight have been shown to be an implementing RKTG pairs in low pass filter circuits by varying the aspect ration of MOSFETs manufactured at 45nm,90nm,and 180nm technologies. this survey is valuable resource for engineers and scientists study in signal processing and communication systems since it offers a through review of low pass filters and their uses

Coacervate Microdroplets as Synthetic Protocells for Cell Mimicking and Signaling Communications.

Synthetic protocells are minimal systems that mimic certain properties of natural cells and are used to research the emergence of life from a nonliving chemical network. Currently, coacervate microdroplets, which are formed via liquid-liquid phase separation, are receiving wide attention in the context of cell biology and protocell research; these microdroplets are notable because they can provide liquid-like compartment structures for biochemical reactions by creating highly macromolecular crowded local environments. In this review, an overview of recent research on the formation of coacervate microdroplets through phase separation; the design of coacervate-based stimuli-responsive protocells, multichamber protocells, and membranized protocells; and their cell mimic behaviors, is provided. The simplified protocell models with precisely defined and tunable compositions advance the understanding of the requirements for cellular structure and function. Efforts are then discussed to establish signal communication systems in protocell and protocell consortia, as communication is a fundamental feature of life that coordinates matter exchanges and energy fluxes dynamically in space and time. Finally, some perspectives on the challenges and future developments of synthetic protocell research in biomimetic science and biomedical applications are provided.

Using acoustic signals for demonstrating key signal processing and communication systems concepts

In this talk, I will highlight the importance of reinforcing mathematical concepts in signal processing and communication systems theory with Matlab-based data analysis. In particular, I will provide examples and demos of homework and project problems I assigned in my linear systems and communication systems courses, and discuss how it helped the students learn in an agile hybrid virtual setting during the pandemic, and whether repeating the same (or similar) problems in an in-person or hybrid setting made a difference. I will also discuss the importance of playing with real-world acoustic signals, and lessons learned, including changes I made in the problem assignments based on student feedback, student performance, and classroom discussions.

Novel Double Modular Redundancy Based Fault-Tolerant FIR Filter for Image Denoising

In signal processing and communication systems, digital filters are widely employed. In some circumstances, the reliability of those systems is crucial, necessitating the use of fault tolerant filter implementations. Many strategies have been presented throughout the years to achieve fault tolerance by utilising the structure and properties of the filters. As technology advances, more complicated systems with several filters become possible. Some of the filters in those complicated systems frequently function in parallel, for example, by applying the same filter to various input signals. Recently, a simple strategy for achieving fault tolerance that takes advantage of the availability of parallel filters was given. Many fault-tolerant ways that take advantage of the filter’s structure and properties have been proposed throughout the years. The primary idea is to use structured authentication scan chains to study the internal states of finite impulse response (FIR) components in order to detect and recover the exact state of faulty modules through the state of non-faulty modules. Finally, a simple solution of Double modular redundancy (DMR) based fault tolerance was developed that takes advantage of the availability of parallel filters for image denoising. This approach is expanded in this short to display how parallel filters can be protected using error correction codes (ECCs) in which each filter is comparable to a bit in a standard ECC. “Advanced error recovery for parallel systems,” the suggested technique, can find and eliminate hidden defects in FIR modules, and also restore the system from multiple failures impacting two FIR modules. From the implementation, Xilinx ISE 14.7 was found to have given significant error reduction capability in the fault calculations and reduction in the area which reduces the cost of implementation. Faults were introduced in all the outputs of the functional filters and found that the fault in every output is corrected.

Physical Design of 64-bit Multiplier and Accumulator (MAC) Unit Using Vedic Multiplier and CLA Adder

In digital signal processing, communication systems and many other applications, multiplier and accumulator units play a crucial role. This work presents an overview of 64-bit MAC Unit, where Vedic multiplier is used as multiplier unit and compared Carry select adders (CSA) and Carry look-ahead adder (CLA) which must be used for adder unit, accumulator unit consist of Parallel in parallel out (PIPO) shift registers. As a result, CLA adder to be more effective in terms of lower delay by comparing with other adders. The MAC Unit was modelled using Verilog-HDL, where its functional verification and synthesized was done using Intel Quartus Prime 21.1, which was simulated on Questa Intel FPGA 21.1. Further GDSII file was created using the cadence tool with the help of Incisive for functional simulation, Genus for synthesis and pre-layout timing analysis, and innovus for physical design. Entire study was carried out in 180nm technology from RTL-GDSII. The delay, power, area was monitored, the memory usage, Pre-Clock Tree Synthesis, Post-Clock Tree Synthesis (CTS) were noted before and after optimization of design.

Field programmable gate arrays implementation of different standard deviation estimation techniques

Additive white Gaussian noise level estimation has found its application in many fields such as biomedical signal processing, communication system, and image processing. Many methods have been proposed with different output accuracy, system complexity, power consumption, and speed. In this paper, three of the most well-known and largely used algorithms (median based, root mean square (RMS) based, and P84 based methods) have been implemented and investigated in a full comparison between them to find their advantage and disadvantage, and the suitability of each method for a specific application. The three designs are created using Xilinx system generator (XSG) and implemented on Xilinx field programmable gate arrays (FPGA) development board with Zynq series "XC7Z020-1CLG484", to evaluate the design's performance and the results are discussed in the paper.

Identification and Evaluation of Urban Rail Transit Operation Risk Factors Based on Entropy-AHP Hybrid Constrained DEA Method

The whole society is increasingly aware of the importance of urban rail transit (URT) safety and risk management. In order to correctly identify and evaluate the risk factors of URT operation and then classify and take differential measures to deal with the risk factors, the risk sources of URT accidents were analyzed by fault tree analysis and the URT operation risk evaluation index system concerning 8 categories and 40 risk sources were constructed. The DEA (data envelopment analysis) method with entropy-AHP hybrid constraint was established, and the probability and consequences of URT operation risk were taken as decision variables to evaluate and rank various risk factors. The results show that decision-making units (DMU) 1and 2， namely, vehicle system failure and signal communication system failure, are at the largest Pareto risk units, the probability of risk can be reduced by 50.08% and 41.7%, and the risk consequences can be reduced by 35.57% and 46.83%, respectively. Staff factors and environment and management factors are the other two units closest to the maximum risk surface. A risk factor distribution matrix was established, and 40 risk factors are divided into risk factors, leverage risk factors, conventional risk factors, and influential risk factors, which provide a basis for the classification and policy of rail transit risk management.

Low-Noise Phase-sensitive Parametric Amplifiers Based on Integrated Silicon-Nitride-Waveguides for Optical Signal Processing

Low-noise optical amplification has been a long-lasting research topic in various fields including communication, metrology and quantum optics. Here we report optical signal processing at different wavelengths enabled by a low-noise optical phase-sensitive amplifier (PSA) using a single compact integrated silicon nitride photonic waveguide. For 10 Gbit/s non-return-to-zero optical signals with central wavelengths tuned in the telecommunication band, the waveguide-based PSA exhibits a gain of more than 10 dB and a noise figure of about 1.2 dB when the coupling losses are neglected. For a bit-error-rate level of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−9</sup> , penalties of less than 0.8 dB for all channels are observed after the signals propagating through the chip-based PSA, which may be due to the distortions in the few-mode waveguide. These experimental results generally agree with theoretical prediction and indicate that silicon-nitride-based PSAs are promising for the next generation of broadband optical signal processing and communication systems.

Construction of complex environment speech signal communication system based on 5G and AI driven feature extraction techniques

Construction of complex environment speech signal communication system based on 5G and AI driven feature extraction techniques

Simulation of LMS based adaptive noise cancellation using Labview

The audio signals processed in the signal measurement systems are inevitably susceptible to unwanted noise which significantly affects the quality of the signal and the overall performance of the signal communication systems. Due to its' random and unpredictable nature, the amount of noise in signals has proven to be a significant issue in designing these systems and recently has been a trending research topic. In this regard, the active noise cancellation method has proven to be an effective technique for eliminating the noise effects on signal processing. The concept of active noise cancellation is based on the application of adaptive filters and algorithms proposed to reduce the signal corruption and distortion caused by the noise due to the principle of destructive interference. In this paper a simulation model of active noise reduction technique using the LMS (Least Mean Square) algorithm in Labview is presented. The purpose of the work is to investigate the noise cancellation effect on a recorded audio file in terms of analyzing the audio file before and after filtering out the noise by using the LMS algorithm and discuss the results thereof.