Advanced Digital Signal Processing Research Articles

Performance Investigation of Joint LUT and GS Algorithm at the Transceiver for Nonlinear and CD Compensation

In order to meet the increasing requirements of speed and distance, an advanced digital signal processing (DSP) algorithm is preferred without changing the system structure in intensity modulation and the direct detection (IM/DD) system. As the transmission distance increases, the power fading induced by dispersion must be mitigated. In addition, linear and nonlinear inter symbol interference (ISI) introduced by bandwidth limitation and device imperfections becomes an obstacle to achieving higher capacity. The Gerchberg–Saxton (GS) algorithm was recently used to compensate for dispersion. In this paper, GS-based pre- and post-compensation schemes in the IM/DD system with nonlinearity were investigated. We investigated and compared the performance of the GS-based pre- and post-compensation algorithm in a 28 GB aud four-level pulse amplitude modulation (PAM-4) transmission over 40 km standard single-mode fiber (SSMF). The bit error rate (BER) achieved a threshold of 3.8 × 10−3 using look-up-table (LUT), FFE, and the GS-based pre-compensation algorithm without iterations. Turning to the GS-based post-compensation scheme, 80 iterations are needed. However, the demand for FFE is reduced. The algorithm selection depends on the tolerance of the transmitter or receiver complexity in specific scenarios. The joint LUT and GS-based pre-compensation algorithm may be a preferable approach in scenarios where a low-complexity receiver is desired.

A review in advanced digital signal processing systems

Digital Signal Processing (DSP) is a powerful technology that helps in making sense of various signals, like sounds and images, using computers. This review paper explains the meaning of DSP, shows how it works to process and enhance signals. It explores the wide range of signal processing methods, categorizing them from basic noise reduction to advanced machine learning algorithms, and how they are used today to improve the quality of audio, images, medical data, and other control systems. The paper further examines into signal processing techniques, providing a comprehensive understanding of the diverse methodologies employed in DSP applications. Additionally, it addresses not only the advancements but also the drawbacks associated with advanced DSP systems, offering insightful recommendations for overcoming challenges and optimizing performance. This review also includes categories of DSP methods, providing a structured overview of the different approaches within the field. It offers a clear and concise understanding of DSP, its practical uses, and its exciting potential in the digital age

Sound and Noise Sources in Sonotubometry: An Investigation of Eustachian Tube Assessment

This research aims to enhance the understanding of the acoustic processes occurring during sonotubometry, a method used to assess the Eustachian tube (ET) function. Recent advancements in digital signal processing enable a more comprehensive data analysis. In this project, a silicone model of the ET was developed to systematically study the existing noise and sound sources. These measurements were then compared with recordings from human subjects. Three distinct ’noise sources’ were identified, which can influence the assessment of the ET opening using transmission measurements of the imposed signal: sound leakage from the speaker, a clicking noise at the initiation of ET opening, and rumbling/swallowing noise. Through spectral analysis, it was also possible to ascertain the spectral and temporal occurrence of these sound and noise types. The silicone model exhibited remarkable similarity to the healthy human ET, making it a robust experimental model for investigating the acoustics of sonotubometry. The findings underscore the significance of delving deeper into the analysed sound, as the noise occurring during sonotubometry can be easily misconstrued as an actual ET opening. Particularly, careful consideration is warranted when evaluating data involving clicking and swallowing noise.

Online digital compensation of pump dithering induced phase and amplitude distortions in transmission links with cascaded fibre-optical parametric amplifiers

We present an advanced online digital signal processing (DSP) method for correcting the phase and amplitude distortions caused by the phase modulation of the pump source and its interaction with the dispersive fibre channel in transmission systems using cascaded fibre-optical parametric amplifiers. The proposed algorithm is numerically demonstrated to achieve significant (up to 3.7 dB for a four-tone pump-phase modulation scheme) Q2-factor performance improvement over conventional DSP in 16 quadrature-amplitude modulation signal transmission.

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.

Low-complexity and low-latency equalization technique - probabilistic noise cancellation.

Both inside data centers (DCs) and in short optical links between data centers (DC campuses), intensity-modulation and direct-detection (IMDD) systems using four-level pulse amplitude modulation (PAM4) will dominate this decade due to low transceiver price and power consumption. The next DC transceiver generation based on 100 Gbaud PAM4 will require advanced digital signal processing (DSP) algorithms and more powerful forward error correction (FEC) codes. Because of bandwidth limitations, the conventional DC DSP based on a few-tap linear feed-forward equalizer (FFE) is likely to be upgraded to more complex but still low-complexity Volterra equalizers followed by a noise whitening filter and either a maximum likelihood sequence estimation (MLSE) or a maximum a posteriori probability (MAP) algorithm. However, stringent power consumption and latency requirements may limit the use of complex algorithms such as decision feedback equalizer (DFE) or MLSE/MAP in DC networks (DCN). In this paper, we introduce a low-complexity, low-latency algorithm based on a feedforward structure, yielding a performance between DFE and MLSE. We call the novel equalization algorithm probabilistic noise cancellation (PNC), since it weights noise patterns based on their probabilities in the presence of bandwidth limitations. The probabilistic weighting is efficiently exploited in correcting correlated errors caused by noise coloring in the FFE.

Analyzing correlation with BER: Constellation diagrams across various modulation modes and FDM/OFDM

Over the last two decades, owing to rapid advancements in digital signal processing and integrated circuit technology, Frequency Division Multiplexing (FDM) and Orthogonal Frequency Division Multiplexing (OFDM) have emerged as pivotal technologies for wireless multimedia communication. Research reveals that coupling OFDM with diverse modulation modes aids in mitigating the Bit Error Rate (BER) during transmission. Nonetheless, a comprehensive elucidation remains absent regarding the interplay between constellation diagrams and BER, as well as the correlation between FDM and BER. Thus, the primary focus of this research is to dissect the correlation between BER and constellation diagrams for distinct modulation methodologies, while also scrutinizing the impact of FDM on BER. The research methodology adopted herein entails two main steps: First, gathering papers pertinent to constellation diagrams, BER, FDM, and OFDM technology. Second, leveraging survey and literature analysis methodologies for thorough examination. The findings highlight that diverse constellation diagram designs yield disparate BER outcomes post demodulation. Foremost among the influential factors on FDM and OFDM technology BER are distinct Inter-Carrier Interference (ICI) patterns and the quantity of subcarriers stemming from signal wave side lobes. To address the BER challenge, a prospective avenue involves refining the selection of constellation diagram styles for demodulation, leveraging an understanding of constellation diagram traits. Furthermore, future research endeavors should delve deeply into co-channel interference and adjacent channel interference to contribute effectively towards BER reduction and augmenting channel reliability.

SIMULATION MODEL OF AN ADARTIVE DIGITAL FILTER BASED ON THE LEAST SQUARES METHOD

In accordance with contemporary requirements in the fields of mobile and embedded telecommunications and electronics, there is a growing need for faster, smaller, and energy-efficient digital electronic devices (DEDs). These devices include microcontrollers, digital signal processors, and programmable logic integrated circuits (FPGAs).
 Utilizing DEDs involves the hardware execution of advanced digital signal processing (DSP) algorithms tailored to the specific architecture of the electronic device. To expedite the design process when directly implementing DSP algorithms in hardware, simulation models are generated to facilitate optimizing the design during the creation of the programming component for FPGAs.
 The paper discusses the outcomes of an investigation into an adaptive filter (AF) model that relies on the recursive least squares method (RLS). During the simulation, an analysis of the time and frequency parameters of the AF model was conducted. It was determined that the quality of the filtering process reaches a plateau at the 28th order, and further increasing the AF order does not lead to a significant improvement in signal filtering. Instead, it results in an increased demand for hardware resources. Furthermore, during the verification of the proposed simulation model, an AF-based noise reduction system was simulated. The total harmonic distortion (THD) level for the built-in AF unit was found to be 1.05 % that serves as confirmation of the effectiveness of the developed AF unit.
 Therefore, through this investigation, the most suitable order for the AF has been identified. This choice will enable a more effective utilization of FPGA resources when implementing the AF in hardware. The study results validate the accuracy and effectiveness of the hardware-centric simulation model developed, while also demonstrating the hardware-oriented architecture of the adaptive RLS filter for its forthcoming implementation on FPGA.

Implementation of Digital Signal Processor for Pulse Doppler Radar

This paper presents the design and implementation of a digital signal processor (DSP) board, utilizing a TMS320C50 family DSP chip, for pulse-Doppler radar systems. Pulse-Doppler radar systems often encounter challenges such as strong clutter, noise, and jamming in dealing with echoes. To overcome these challenges, advanced digital signal processing techniques are employed. The main objective of this paper is to introduce a cost-effective signal processing solution that significantly enhances the performance of the radar system and brings it up to speed with modern radar technologies. The hardware described in this work can also be effectively utilized for implementing various types of signal processing algorithms. Additionally, as a secondary objective, the paper presents the digital realization of a radar detector. Traditionally, this detector was constructed using an analog Doppler filter bank. However, in this work, it is digitally implemented using N digital filters in place of the analog bank. By utilizing the designed DSP board and implementing the radar detector digitally, this paper demonstrates the potential for improved performance and efficiency in pulse-Doppler radar systems. The advancements made in this work contribute to the development of cost-effective and technologically advanced radar systems. The research results are presented for four different wind conditions, showcasing the effectiveness of the proposed approach. Furthermore, the paper suggests an algorithm that combines parametric and non-parametric techniques and provides a detailed explanation of its implementation. Finally, using the non-parametric technique, the probability of detection curves (PD) are simulated with respect to the signal-to-clutter ratio (SCR) for each wind condition, and the simulation results are depicted and compared. The achievements of this paper include the proposal of an efficient approach for clutter suppression in ground surveillance pulse Doppler radar, the comparison of different clutter suppression algorithms, and the development of an algorithm that combines parametric and non-parametric techniques. The simulation results provide valuable insights into the performance of the proposed algorithms under different wind conditions.

Active Noise Control in The New Century: The Role and Prospect of Signal Processing

Since Paul Leug's 1933 patent application for a system for the active control of sound, the field of active noise control (ANC) has not flourished until the advent of digital signal processors forty years ago. Early theoretical advancements in digital signal processing and processors laid the groundwork for the phenomenal growth of the field, particularly over the past quarter-century. The widespread commercial success of ANC in aircraft cabins, automobile cabins, and headsets demonstrates the immeasurable public health and economic benefits of ANC. This article continues where Elliott and Nelson's 1993 Signal Processing Magazine article [1] and Elliott's 1997 50th anniversary commentary [2] on ANC left off, tracing the technical developments and applications in ANC spurred by the seminal texts of Nelson and Elliott (1991), Kuo and Morgan (1996), Hansen and Snyder (1996), and Elliott (2001) since the turn of the century. This article focuses on technical developments pertaining to real-world implementations, such as improving algorithmic convergence, reducing system latency, and extending control to non-stationary and/or broadband noise, as well as the commercial transition challenges from analog to digital ANC systems. Finally, open issues and the future of ANC in the era of artificial intelligence are discussed.

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.

Acoustical verification of binaural features in hearing aids

Hearing aid verification systems are designed to verify sound pressure levels in a patient’s ear canal, as well as ensure hearing aid features are performing to company specifications. In addition to verifying sound output, verification systems can analyze frequency specific compression, prescription targets, directional microphones, noise reduction performance, etc. However, current verification systems are unable to verify several advanced digital signal processing (DSP) features that companies have included in their hearing aids over the recent years. Particularly, binaural features which require both hearing aids to be analyzed simultaneously to measure interaural cues. Here, interaural cues were analyzed from recordings made on an acoustic manikin in an anechoic chamber across various noise reduction and directional microphone features using open-fit and occluding coupling compared to an unaided condition. During data collection, settings in the fitting software did not always align to hearing aid coupling (i.e., open versus occluding dome conditions), an error likely to occur clinically. For some noise reduction hearing aid conditions, a large interaural level difference (ILD) was introduced to one hearing aid, distorting the sound source location. ILD cues measured here, across different DSP and coupling conditions, suggest verification protocols should include additional features, such as binaural measurements.

Ultrasonic vibration measurement using heterodyne interferometry and SDR phase meter

Ultrasonic vibration measurement and the development of ultrasonic vibration sensors have a significant impact on underwater pattern detection, providing good support for the exploitation and usage of marine resources. Advanced digital signal processing algorithms improve mechanical displacement measurements using ultrasonic speed and pm-level interferometers in real-time. In recent years, developing digital algorithms and employing low-cost software-defined radio (SDR) software applied to communication systems and other general-purpose systems with flexible solutions are essential in modern industrial applications. Specifically, the SDR can be consistent with real-time phase-change measurements of MHz-frequency interference signals for a heterodyne interferometer. This paper combines a heterodyne interferometer and a real-time SDR phase meter, demonstrating an ultrasonic vibration instrument's high-speed vibrating measurement capabilities. A double-pass interferometer is implemented to produce interference signals modulated with a sine waveform phase change associated with a tool's ultrasonic vibrating displacement, calculated by the phase meter's quadrature demodulation algorithm. The measurement results show that the system detects the sine-wave vibration trajectory generated by the vibrator at a frequency of 20 kHz and an amplitude of ~460 nm. The principle of the measurement system, instrumentations, experiments, and results are discussed in the paper.

Broadband Photon-Assisted Terahertz Communication and Sensing

Terahertz band (0.1 to 10 THz) with high carrier frequency and large available bandwidth has become a promising candidate to meet the 100 Gbit/s or even 1 Tbit/s data rate required by the future six-generation (6G) mobile communication networks. Compared with the all-electrical methods to generate terahertz signals, the photon-assisted technology can break the bottleneck of the bandwidth limit of the electronics devices, and generate the terahertz signal with high frequency, large bandwidth, flexible tunability and easy integration with the large capacity fiber link. In this paper, we introduce the typical methods to generate terahertz signals based on the photon-assisted technology, and review the representative achievements in different areas of terahertz communication, such as the large capacity terahertz transmission, the long distance terahertz transmission, the real-time terahertz communication, and the integrated terahertz sensing and communication. Based on the photon-assisted technology and various key techniques, devices and advanced digital signal processing (DSP) algorithms, we have obtained many great achievements in broadband terahertz communication and sensing, and the experimental setups and results have also been demonstrated in detail.

High-Speed and Long-Distance Photonics-Aided Terahertz Wireless Communication

Terahertz (THz) photonics technique can break through the bandwidth limitation of electronic mixing method and be seamless integrated with optical access networks, which has bright prospects in future 6G broadband communication. However, due to the bottleneck of photoelectric conversion efficiency of uni-travelling photodiode (UTC-PD), the power of the generated THz-wave signal is usually only in the microwatt level, and the THz-wave wireless transmission distance is short. In this paper, we summarize the key techniques we use to extend the wireless range for photonics-aided THz-wave communication, which includes THz-wave amplifiers and antennas, heterodyne detection, probabilistic shaping (PS) technique as well as advanced digital signal processing (DSP). Meanwhile, we report our recent research including 104\200\400-m photonics-aided THz-wave wireless transmission records.

Key Technologies for High-Speed Si-Substrate LED Based Visible Light Communication

Nowadays, the demand for high-speed information transmission is increasing rapidly. Visible light communication (VLC) based on light-emitting diodes (LEDs) is supposed as a potential candidate for future 6G communication networks. However, as an emerging field of optical communications, the data rate of VLC systems is restricted to the extremely limited modulation bandwidth and nonlinear characteristics of optoelectronic devices. In this paper, we outline the state of art and challenges of VLC, and introduce the key technologies for high-speed Silicon (Si) -substrate LED-based VLC systems. Based on an optimized integrated 4×4 8-wavelength LED array and advanced digital signal processing (DSP) methods, we demonstrate an ultrahigh-speed VLC system. Digital Zobel network (DZN) pre-equalization and transfer learning bidirectional gate recurrent unit (TL-Bi-GRU) based post-equalization are proposed to mitigate linear and nonlinear impairment. The yellow and green LEDs are especially enhanced in high-efficacy, and achieve the impressive data rates of 3.45Gbit/s, and 3.83Gbit/s respectively, which is a remarkable improvement. The achievable overall data rate of the device is 28.93 Gbit/s. As far as we know, it's the highest data rate achieved by a single-chip Si-substrate LED array.

Comparison of algorithms for contrast enhancement based on triangle orientation discrimination assessments by convolutional neural networks

Within the last decades, a large number of techniques for contrast enhancement has been proposed. There are some comparisons of such algorithms for few images and figures of merit. However, many of these figures of merit cannot assess usability of altered image content for specific tasks, such as object recognition. In this work, the effect of contrast enhancement algorithms is evaluated by means of the triangle orientation discrimination (TOD), which is a current method for imager performance assessment. The conventional TOD approach requires observers to recognize equilateral triangles pointing in four different directions, whereas here convolutional neural network models are used for the classification task. These models are trained by artificial images with single triangles. Many methods for contrast enhancement highly depend on the content of the entire image. Therefore, the images are superimposed over natural backgrounds with varying standard deviations to provide different signal-to-background ratios. Then, these images are degraded by Gaussian blur and noise representing degradational camera effects and sensor noise. Different algorithms, such as the contrast-limited adaptive histogram equalization or local range modification, are applied. Then accuracies of the trained models on these images are compared for different contrast enhancement algorithms. Accuracy gains for low signal-to-background ratios and sufficiently large triangles are found, whereas impairments are found for high signal-to-background ratios and small triangles. A high generalization ability of our TOD model is found from the similar accuracies for several image databases used for backgrounds. Finally, implications of replacing triangles with real target signatures when using such advanced digital signal processing algorithms are discussed. The results are a step toward the assessment of those algorithms for generic target recognition.

Optimal Adaptive Waveform Design Utilizing an End-to-End Learning-Based Pre-Equalization Neural Network in an UVLC System

Visible light communication (VLC) has emerged as a promising communication method in the special field of 6G, such as intersatellite communication (ISC) and underwater wireless optical communication (UWOC). Green light-emitting diode (LED)-based underwater visible light communication (VLC) is considered a potential candidate for UWOC of mobile autonomous underwater vehicle (AUV) and remotely operated underwater vehicle, particularly in coastal and harbor environments. However, due to bandwidth limitations and variable underwater channels, implementing high-speed underwater VLC remains a challenge. In this paper, a neural network-based auto equalization model (NNAEM) using end-to-end learning is proposed to achieve a high-speed underwater VLC link with a bandwidth-limited green LED. The entire NNAEM includes a neural network-based channel model, a pre-equalization neural network, and a post-equalization neural network. Based on the data-driven channel model, our auto equalization (AE) method can dynamically pre-equalize the discrete multitone (DMT) modulated signal in different bandwidth-limited cases and various nonlinearity cases. An underwater VLC link with a data rate of 3.451 Gbps and a transmission distance of 1.2 m is experimentally demonstrated by employing the proposed NNAEM under the hard decision-forward error correction (HD-FEC) threshold of 3.8 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">−3</sup> . The data rate improvement is up to 30.4% compared to other advanced digital signal processing (DSP) methods. The scenario adaptation and robustness of the NNAEM are also verified in the experiments, which demonstrate that the NNAEM can serve an important role in underwater high-speed VLC transmission.

Recent Advances in Coherent Optical Communications for Short-Reach: Phase Retrieval Methods

Short-reach transmission systems traditionally utilize intensity modulation (IM) at the transmitter and direct detection (DD) at the receiver due to their cost-effectiveness, small footprint, and low power consumption. However, with the exponential increase in bandwidth demand, coherent optical communication systems have become necessary for long-haul distances, requiring application-specific integrated circuits (ASIC) and advanced digital signal processing (DSP) algorithms coupled with high-speed digital-to-analog and analog-to-digital converters to achieve Tbit/s speeds. As coherent technology matures, it will eventually become feasible for short-reach transmission. In this context, self-coherent systems have emerged as an intermediary solution, offering advantages over traditional IM/DD systems. While comprehensive review studies exist on self-coherent transceivers, they do not cover recent advances in phase retrieval methods for short-reach optical communications. This review article highlights recent developments in cost-effective self-coherent detection for short-reach systems through comparing the benefits of single sideband (SSB) transmission and Kramers-Kronig detection to carrier-assisted phase retrieval, the Gerchberg-Saxton (GS) algorithm, and the transport of intensity equation (TIE) method.

The 1980s—The glory years for the development of active noise and vibration control

In the field of acoustics in general, and structural acoustics in particular, a new “hot topic” seems to burst upon the scene once or twice each decade. Everyone wants to get involved, numerous sessions on the topic appear at our meetings, and progress on the topic seems to leap forward—at least until the next hot topic comes along. In the 1980s, active noise and vibration control burst upon the scene, becoming the then current hot topic, as advances in digital signal processing made the technique much more attractive. The number of publications and presentations on the topic exploded, and active control was the bandwagon that everyone wanted to be on. The author was just beginning his career during this time period and was able to begin pursuing research on this topic in the early stages of the explosion. The intense interest in the topic continued until about the mid-1990s. This paper will review some of that early activity, what advances were made, why the interest seemed to decline in the 1990s, and what the current state of the discipline is as the research has continued to slowly move forward over the intervening years.