Advanced Digital Signal Processing Research Articles

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.

Localization and externalization of speech through hearing aids with adaptive features

Hearing aids with advanced digital signal processing features that analyze acoustic scenes can amplify wanted sounds (e.g., speech) while utilizing complex noise reduction features to attenuate unwanted sounds (e.g., noise). These adaptive features can be programmed to be more or less aggressive in order to prioritize listening comfort or speech detail. Importantly, these adaptive features may alter the interaural cues of relevant target talkers located in front of the listener, causing unwanted effects on spatial perception. Here, we explored these effects. Spondees were presented from 11 different loudspeakers (located between ±75° azimuth separated by 15°) in an anechoic chamber. Binaural recordings were obtained from the ear canals of a Bruel &amp; Kjaer Head and Torso Simulator, which was fitted with Oticon More hearing aids. The recordings were then presented over headphones to listeners, who indicated the perceived direction and degree of externalization of the spondees. Several conditions were tested, which differed in the acoustics of the room (anechoic and simulated reverberation), the background (quiet and noise), and the hearing-aid coupling (unaided, open-fit, and occluded). Behavioral data will be compared to measured interaural cues in the corresponding binaural recordings.

Advanced DSP-Based Monitoring for Spatially Resolved and Wavelength-Dependent Amplifier Gain Estimation and Fault Location in C+L-Band Systems

The development of efficient anomaly detection schemes is a key element for the implementation of autonomous optical networks as they can help telecom operators to automate the location of defective devices and track the overall performance of the network infrastructure. In that regard, the exploitation of receiver based digital signal processing (DSP) for optical performance monitoring has shown to be a promising enabler for detection of spatially resolved and wavelength-dependent properties and anomalies in optical fiber links. In this work, we study the benefits of applying DSP-based longitudinal power estimation on multiple wavelength division multiplexing (WDM) channels allocated in the optical grid to infer wavelength-wise characteristics of a C+L-band optical line system. In that context, we show that the applied scheme can successfully recreate a visualization of the spatial evolution of the gain tilt imposed by in-line optical amplifiers. Additionally, we propose the utilization of advanced DSP tools based on wavelet-denoising to enhance the performance of an anomaly detection approach. The proposed method not only can improve accuracy of the fault location, by reducing positioning uncertainty, but it also delivers more uniform readings of the anomaly signatures.

DRL-Based Joint Path Planning and Jamming Power Allocation Optimization for Suppressing Netted Radar System

For jammer formations, due to advanced digital signal processing and precise synchronization, suppressing and penetrating netted radar systems face more challenges than ever. In this letter, a deep reinforcement learning-based joint path planning and jamming power allocation optimization (DRL-JPPAO) method is proposed. DRL-JPPAO models the penetration operation by a Markov Decision Process and utilizes the Proximal Policy Optimization algorithm to learn optimal sequential actions, which consist of waypoints and jamming power allocation matrices, to solve it. The learning process is guided by a reward function that depends on the success or failure of penetration and the distance to the target. Empirical results with a newly developed environment show that DRL-JPPAO can learn optimal paths and jamming power allocation strategies jointly, accomplishing the penetration operation effectively and elegantly.

Machine learning enabled digital compensation of phase-to-amplitude distor-tion in fibre-optical parametric amplifier based transmission links

We numerically demonstrate an advanced digital signal processing method for compensating the phase-to-amplitude distortion conversion caused by the interaction of the phase noise induced by pump dither-ing with the dispersive fibre channel in fibre-optical parametric amplifier based transmission systems.

Quantifying Cognitive Workload Using a Non-Contact Magnetocardiography (MCG) Wearable Sensor

Quantifying cognitive workload, i.e., the level of mental effort put forth by an individual in response to a cognitive task, is relevant for healthcare, training and gaming applications. However, there is currently no technology available that can readily and reliably quantify the cognitive workload of an individual in a real-world environment at a seamless way and affordable price. In this work, we overcome these limitations and demonstrate the feasibility of a magnetocardiography (MCG) sensor to reliably classify high vs. low cognitive workload while being non-contact, fully passive and low-cost, with the potential to have a wearable form factor. The operating principle relies on measuring the naturally emanated magnetic fields from the heart and subsequently analyzing the heart rate variability (HRV) matrix in three time-domain parameters: standard deviation of RR intervals (SDRR); root mean square of successive differences between heartbeats (RMSSD); and mean values of adjacent R-peaks in the cardiac signals (MeanRR). A total of 13 participants were recruited, two of whom were excluded due to low signal quality. The results show that SDRR and RMSSD achieve a 100% success rate in classifying high vs. low cognitive workload, while MeanRR achieves a 91% success rate. Tests for the same individual yield an intra-subject classification accuracy of 100% for all three HRV parameters. Future studies should leverage machine learning and advanced digital signal processing to achieve automated classification of cognitive workload and reliable operation in a natural environment.

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.

Support Vector Machine-Based Soft Decision for Consecutive-Symbol-Expanded 4-Dimensional Constellation in Underwater Visible Light Communication System

Nowadays, underwater visible light communication (UVLC) has become one of the key technologies for high-speed underwater wireless communication. Because of the limited modulation bandwidth and nonlinearity of the optoelectronic devices in the UVLC system, the combination of inter-symbol interference and nonlinear impairment will inevitably degrade the transmission performance. Advanced digital signal processing methods including equalization and decoding are required. In the past few years, Support vector machine (SVM) has been widely investigated in quadrature amplitude modulation (QAM) for soft decision in the decoding process. However, previous works only consider 2-dimensional (2-D) separate symbol, ignoring the correlation between consecutive symbols. In this paper, we propose to use SVM for soft decision with a 4-dimensional (4-D) constellation by concatenating two consecutive symbols. To deal with the increasing computational complexity in the SVM training phase, bit-based binary SVM multi-class strategy and an edge-detection-based data pre-processing method are employed. In this paper, we demonstrate a carrierless amplitude and phase (CAP) 16-QAM UVLC system. Experimental results indicate that the performance is greatly improved when using consecutive-symbol-expanded 4-D constellation with SVM for soft decision.

Review of Fundamental Active Current Extraction Techniques for SAPF.

The field of advanced digital signal processing methods is one of the fastest developing scientific and technical disciplines, and is important in the field of Shunt Active Power Filter control methods. Shunt active power filters are highly desirable to minimize losses due to the increase in the number of nonlinear loads (deformed power). Currently, there is rapid development in new adaptive, non-adaptive, and especially hybrid methods of digital signal processing. Nowadays, modern methods of digital signal processing maintain a key role in research and industrial applications. Many of the best practices that have been used to control shunt active power in industrial practice for decades are now being surpassed in favor of new progressive approaches. This systematic research review classifies the importance of using advanced signal processing methods in the field of shunt active power filter control methods and summarizes the extant harmonic extraction methods, from the conventional approach to new progressive methods using genetic algorithms, artificial intelligence, and machine learning. Synchronization techniques are described and compared as well.

104 Meters Photonics-Aided Terahertz Wireless Transmission Without Terahertz Amplifier

In this letter, we experimentally demonstrate a long-distance, large-capacity and photonics-aided wireless terahertz (THz) transmission system without THz amplifier. Using dielectric lenses and advanced digital signal processing (DSP), we have achieved 124 Gbit/s signal transmission over 54 meters wireless distance and 44 Gbit/s signal transmission over 104 meters wireless distance. For all we know, this is the longest wireless distance that can be achieved by using dielectric lenses without any THz amplifiers.

Wireless transmission of a 200-m PS-64QAM THz-wave signal using a likelihood-based selection radius-directed equalizer.

Based on a photonics-aided scheme, we achieve an experimental demonstration of a, to the best of our knowledge, record-breaking 200-m terahertz (THz)-wave wireless delivery at 335 GHz with the aid of a pair of high-gain polytetrafluoroethylene (PTFE) lenses. By using a 10-GBaud probabilistically shaped 64-ary quadrature amplitude modulation (PS-64QAM) signal and advanced digital signal processing (DSP) including a likelihood-based selection radius-directed equalizer (LBS-RDE), the single-carrier net bit rate of the wireless delivery reaches 44 Gbit/s. High-speed THz-wave communication with up to 200-m wireless distance is successfully realized based on a photonics-aided scheme for the first time.

Photonics-Aided Terahertz-Wave Wireless Communication

To meet the upcoming 6G communications challenges, terahertz-wave (THz-wave) wireless data transmission over 100 Gb/s is urgently needed in the short term. However, advanced digital signal processing (DSP) technologies suitable for millimeter-wave (mm-wave) bands cannot satisfy the requirements; increasing the carrier frequencies for more spectra is essential. Photonics-aided THz-wave generation (PTG) technology has become a valid way to solve the bandwidth bottleneck. New progress has been made in PTG by using optical frequency combs and optical modulators. The application of DSP technology for heterodyne detection can not only overcome the nonlinear effect in photoelectric devices but also enhance the receiver sensitivity and spectral efficiency. Multidimensional multiplexing technology can reduce the baud rate of each subchannel to realize the long-distance transmission of THz-wave signals. In this tutorial, we introduce the key technologies and principles of ultrahigh speed and large capacity THz-wave signal transmission. These technologies can effectively improve the transmission capacity and distance and reduce the bandwidth required by optical and electronic equipment.

Colorless Coherent TDM-PON Based on a Frequency-Comb Laser

Coherent reception becomes an interesting option when data rates in time-division-multiplexed (TDM) passive optical networks (PONs) grow beyond 50 Gbit/s. Controlling the wavelength, i.e., the optical frequency, and the phase of the laser acting as local oscillator (LO) is one of the main technical challenges in the design of coherent TDM PONs. In the optical network units (ONUs), low-cost lasers are required, which come at the expense of wavelength variations and drifts over multiple nanometers due to fabrication imperfections, and temperature variations. This contradicts the requirement of wavelength-stable LOs in coherent receivers. The use of a wavelength locker circuit and a temperature controller is considered as too complex for applications in access networks. In this work, we propose a novel colorless coherent architecture with high resilience to ONU laser wavelength drifts of up to <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 4 nm ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\pm$</tex-math></inline-formula> 0.5 THz) for future 100 Gbit/s PON. It allows the use of distributed feedback lasers at the ONU side. This is rendered possible by generating a frequency comb with carefully chosen free spectral range in a quantum-dash mode-locked laser diode at the optical line terminal. In upstream operation, the frequency comb serves as an LO, whereas the same information is modulated onto all comb lines for the case of downstream. As a result, the ONU laser can drift over the entire comb bandwidth without substantial performance penalty. We experimentally demonstrate downstream and upstream operation with an aggregated raw data rate of 96 Gbit/s, respectively. We further introduce advanced digital signal processing (DSP) methods including a coarse frequency offset compensation (CFOC) and a multiple-input multiple-output (MIMO) equalizer to improve the performance of our concept. We show that the receiver sensitivity can be increased by 3 dB for a high-bandwidth receiver when using a 6 × 2 MIMO equalizer scheme. A 4 × 2 MIMO equalizer scheme enables colorless reception even with a limited-bandwidth receiver.

Mitigation of turbulences induced by air bubbles and performance enhancement in 112 Gbps UWOC link with coherent detection MIMO PDM-QPSK and advanced digital signal processing

Mitigation of turbulences induced by air bubbles and performance enhancement in 112 Gbps UWOC link with coherent detection MIMO PDM-QPSK and advanced digital signal processing

Least Angle Regression-Based Modified Volterra Nonlinear Equalizer for Optical Interconnection System

Advanced digital signal processing (DSP) is viewed as an inevitable technology to deal with nonlinear distortions in cost-sensitive optical interconnection systems. Classic methods such as equalization based on Volterra series turn out to be quite effective solutions to compensate signal impairments. In practical imple-mentations, a great deal of efforts focus on reducing the com-putational complexity. Several model selection and dimensionality reduction approaches have been proposed to simplify the struc-ture, which employ backward strategies. However, the threshold settings for these pruning approaches are environment-sensitive. In this paper, we propose a least angle regression-based nonlinear equalization method (LaNLE). We extend the non-intrusive least angle regression technique to generalized linear models. Through an incremental process by stagewise feature selection and weight fitting, we obtain the low-complexity nonlinear structure with significant feature basis. Experimental verification is performed based on 120 Gbps PAM8-modulated 850 nm VCSEL plus MMF optical link. The results show that, compared to fully-connected Volterra nonlinear equalizer structure (VNLE), up to 60.4% and 70.1% reduction in complexity can be achieved with similar BER performance in back-to-back and 100 m transmission scenarios, respectively. In addition, we experimentally demonstrate 225 Gbps per lane PAM-8 signal transmission over 100 m MMF in a simple and cost-effective implementation manner based on mass-production 850 nm VCSEL and proposed LaNLE method.

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.

Digital Signal Processing for High‐Speed THz Communications

The use of advanced digital signal processing (DSP) technology in the high-speed terahertz (THz) communication can effectively compensate the linear and nonlinear effects of the system and further improve the transmission performance of the system. This paper introduces the principle and application of advanced DSP algorithms such as probability shaping (PS) technology, Volterra series nonlinear compensation algorithm, Kramers-Kronig receiver, look-up table (LUT) pre-distortion compensation technology, pre-equalization and decision-directed least-mean-square equalization algorithm. Combined with DSP algorithms such as PS and LUT pre-distortion, using photon-assisted technology to successfully realize the wireless transmission of vector THz signals higher than 1 Tbit/s on the sub-THz band (D-band) 4 × 4 multiple input multiple output system.