Tapped Delay Research Articles

Two-Stage Clock-Free Time-to-Digital Converter Based on Vernier and Tapped Delay Lines in FPGA Device

This article presents an idea, design and test results of a new time-to-digital converter (TDC) implemented in an FPGA device. The high resolution of 13 ps and measurement range of 3.4 ns are achieved based on a two-stage time interpolation (TI). In the first and second stages of the TI we have used the Vernier delay line and a single tapped delay line, respectively. This solution provides respectable metrological parameters without the need to use a clock signal, and significantly saves the logical resources of an integrated circuit (IC). The proposed method, generally based on two different variants of the discrete delay line, is easy to design and implement in digital ICs. For experimental verification, the TDC was implemented in a single programmable device from family Virtex-7 (Xilinx).

Demonstration of QPSK data correlation and equalization using a tunable optical tapped delay line based on orbital angular momentum mode delays

We demonstrate a tunable optical tapped delay line (OTDL) using delays based on orbital angular momentum (OAM) modes to perform data correlation and equalization for a quadrature phase-shift-keyed (QPSK) signal. The system: (i) creates N signal replicas as N taps on different OAM modes through mode multicasting, (ii) tunes the complex tap weights (i.e., amplitude and phase of the modes), (iii) applies a tunable mode-dependent delay to each replica, and (iv) coherently combines the taps in order to realize the OTDL functions of correlation and equalization. The experiment results: (i) identify the correlation occurrence of a sequence of 2 or 3 symbols in an incoming 10 or 20 Gbaud QPSK signal, and (ii) equalize the distortion caused by chromatic dispersion for a 20-Gbaud QPSK data signal and reduce error vector magnitude (EVM) from ∼25.4 to ∼12.9%.

Arbitrary free spectral range control of optical frequency combs based on an optical tapped delay line structure cascaded with a phase modulator

Arbitrary free spectral range control of optical frequency combs based on an optical tapped delay line structure cascaded with a phase modulator

Tunable optical second-order Volterra nonlinear filter using wave mixing and delays to equalize a 10-20 Gbaud 4-APSK channel.

We experimentally demonstrate a tunable optical second-order Volterra filter using wave mixing and delays. Wave mixing is performed in a periodically poled lithium niobate waveguide with the cascaded sum-frequency generation and difference-frequency generation processes. Compared to conventional optical tapped delay line structures, second-order taps are added through the wave mixing of two signal copies. We measure the frequency response of the filter by sending a frequency-swept sinusoidal wave as the input. The tap weights are tuned with a liquid-crystal-on-silicon waveshaper for different filter configurations. With the additional second-order taps, the filter is able to perform a nonlinear function. As an example, we demonstrate the compensation of a nonlinearly distorted 10-20 Gbaud 4-amplitude and phase shift keying signal.

Cloud Variance Impact on the Voltage and Power Flow of Distribution Networks with Photovoltaic Generators

The present paper aims to investigate the effect of different types of clouds on the photovoltaic power generators and electricity distribution network in which they are connected. The developed methodology classifies solar irradiance data according to the GOES-13 satellite image processing, which contain information regarding the types of clouds. The image processing results are then compared with real solar irradiance data in order to analyze the influence of shading and thus classify the measured data as: clear sky, partly cloudy and cloudy. The OpenDSS software is employed for simulating the varying generation and load profiles using the IEEE 34 bus system as a testbed. The result analysis shows the power flow and electrical losses, as well as the generation profiles impact on voltage levels and the operation of voltage regulating equipment. Voltage fluctuations and tap changes are also analyzed considering different tap delays.

Underwater channel estimation exploiting multipath feature morphology.

Real-time accurate channel estimation has been an ongoing challenge because of diverse oceanic events that cause rapid fluctuations of high-energy multipath activity across the delay spread. This work leverages current compressed sensing and sparse optimization techniques with topological signal processing to improve estimation time and localize channel estimation to salient parts of the delay spread. This work improves the estimation time by tracking the channel as a union of overlapping multipath and other scattering events, which are modeled as "feature braids" in the delay-time domain. A channel feature braid may be intuitively visualized as the topologically connected trajectory of a group of channel delay taps, which represent the support of dominant or persistent scattering events, e.g., surface bounce multipath scattering. We present algorithms that harness support-constrained mixed norm optimization techniques to track the evolving support of channel feature braids. We validate our channel feature tracking algorithm independently in experimental field data as well as BELLHOP channel simulations across a diversity of oceanic conditions. This work shows that braiding used in estimation can improve estimation time and track high-energy events that develop within the delay vs time channel representation.

Artificial neural network based estimation of sparse multipath channels in OFDM systems

In order to increase the transceiver performance in frequency selective fading channel environment, orthogonal frequency division multiplexing (OFDM) system is used to combat inter-symbol-interference. In this work, a channel estimation scheme for an OFDM system in the presence of sparse multipath channel is studied using the artificial neural networks (ANN). By means of ANN’s learning capability, it is shown that how to model and obtain a channel estimate and how it allows the proposed technique to give a better system throughput. The performance of proposed method is compared with the Matching Pursuit (MP) and Orthogonal MP (OMP) algorithms that are commonly used in compressed sensing literature in order to estimate delay locations and tap coefficients of a sparse multipath channel. In this work, we propose a performance- efficient ANN based sparse channel estimator with lower computational cost than that of MP and OMP based channel estimators. Even though there is a slight performance lost in a few simulation scenarios in which we have lower computational complexity advantage, in most scenarios, our computer simulations corroborate that our low complexity ANN based channel estimator has better mean squared error and the corresponding symbol error rate performances comparing with MP and OMP algorithms.

Compensating Dynamic Nonlinearities in LED Photon Emission to Enhance Optical Wireless Communication

LEDs can be modulated to support wireless optical data communication. However, particularly LEDs optimized for illumination act as a non-linear low-pass communication channel. In this paper, we translate the non-linear differential equations for the hole-electron recombination and photon emissions, into a discrete-time model with delay taps and non-linear coefficients. This LED model can be inverted, to actively eliminate or mitigate the non-linear dynamic LED distortion. We propose a further simplification of the compensation circuit that allows us to use a relatively simple structure with only a couple of parameters. We experimentally characterize and measure signals communicated via commercially available illumination LEDs that are also used for LiFi communication. In an Intensity Modulation Direct Detection (IM/DD) system employing Pulse Amplitude Modulation (PAM), we show that the proposed equalizer can effectively widen the measured eye diagram, thereby reduce the error rate or can allow a larger constellation. For Orthogonal Frequency Division Multiplexing (OFDM), the reduction in distortion allows at least a 50% increase in bit rate, even on measured noisy channels. This confirms the suitability of the LED model on which our non-linear equalizer is based. We show how non-linear time-constants can be estimated from electrical measurements on the LED signal. With the proposed parameter estimation, the equalizer converges to appropriate compensation settings, in Minimum Mean Square Error (MMSE) sense.

Dengue control measures via cytoplasmic incompatibility and modern programming tools

The vector borne diseases share a high percentage of the annual deaths reported by the world health organization. Due to the involvement of multiple factors and resistance of the vector to the treatment strategies, it is highly desired to design a safe, efficient and harmless control strategy. A state of the art computational framework for the Wolbachia induced “genetic-control-strategy” has been documented during this research. The process of mating and molecular identification is complex and expensive and different labs around the world are devoted to format a smooth implementation strategy of this approach. During this research, as a first step, data was collected, secondly, dynamic artificial neural networks, with the “tapped delay” lines are used for nonlinear filtering of the data and for the prediction of the parametric values of the novel mathematical model. To study parametric reliance of stable solutions and unstable solution we analyze stability and the corresponding thresholds desired for this study are documented. The study conducted during this research can prove to be useful in future experimental and theoretical studies, aimed to control the vector borne diseases.

A Low-Resources TDC for Multi-Channel Direct ToF Readout Based on a 28-nm FPGA.

In this paper, we present a proposed field programmable gate array (FPGA)-based time-to-digital converter (TDC) architecture to achieve high performance with low usage of resources. This TDC can be employed for multi-channel direct Time-of-Flight (ToF) applications. The proposed architecture consists of a synchronizing input stage, a tuned tapped delay line (TDL), a combinatory encoder of ones and zeros counters, and an online calibration stage. The experimental results of the TDC in an Artix-7 FPGA show a differential non-linearity (DNL) in the range of [−0.953, 1.185] LSB, and an integral non-linearity (INL) within [−2.750, 1.238] LSB. The measured LSB size and precision are 22.2 ps and 26.04 ps, respectively. Moreover, the proposed architecture requires low FPGA resources.

A resource-saving dual channel time-to-digital converter with shared tapped delay line in FPGAs

A resource-saving dual channel time-to-digital converter (TDC) in field programmable gate array (FPGA) is presented in this paper. The presented TDC is formed by cascading a channel waveform generator (CWG) and a tapped delay line. Specifically, the CWG can generate six types of waveforms with different transition edges to propagate on tapped delay line according to the different assertion times of two hit signals. Besides, a pipelined encoding module is designed to detect the positions of multiple transition edges on tapped delay line precisely so that the six types of waveforms can be identified and the two hit signals can be distinguished and measured. Since the measurements of two hit signals share one tapped delay line, the TDC based on CWG (CWG-TDC) is a resource-saving dual channel TDC. To evaluate the performance of CWG-TDC, time intervals from 10ns to 200ns were measured on a Xilinx's 40nm Virtex-6 development board. In CWG-TDC, channel 1 and channel 2 can achieve LSB of 9ps, the highest RMS precision of 6.2ps. The consistency between experimental results and theoretical analysis shows that the presented CWG-TDC can not only achieve high RMS precision but also achieve resource-saving.

A 28-GHz Full-Duplex Phased Array Front-End Using Two Cross-Polarized Arrays and a Canceller

This article proposes a 28-GHz full-duplex (FD) phased arrays, which consists of 64-element transmitting and receiving arrays, and a 28-GHz radio frequency (RF) canceller. The phased arrays are designed with $2\times 2$ beamformer chips, and the transmitter (TX) and receiver (RX) arrays are oriented to have cross polarized configurations for high isolation. The 28-GHz RF canceller is based on an identical $2\times 2$ beamformer chip with two external different delay taps. Since the canceller is located at the input and output ports of arrays instead of antennas, it cannot eliminate the nonlinearities and noises in the phased arrays. Therefore, these nonlinearities and noise in the TX and RX arrays are experimentally analyzed to demonstrate that the proposed cross-polarized arrays have enough isolation to achieve suppression to the level of the RX noise floor. The FD phased-array system at 28.5–29.5 GHz has 57-dB isolation between the TX input and RX output ports, where the cross-polarization improves 10-dB isolation comparing to co-polarization and the RF canceller provide additional 10-dB self-interference (SI) suppression. Also, the nonlinearities and noise components of the received SI signals are lower than the noise floor at the output of the RX array. The system requires only 15.5-dB of additional digital cancellation to reduce the SI to the RX noise floor of 1-GHz bandwidth while maintaining the transmitting EIRP at 41 dBm.

Cost-Effective Multi-Parameter Optical Performance Monitoring Using Multi-Task Deep Learning With Adaptive ADTP and AAH

A cost-effective optical performance monitoring (OPM) scheme is proposed to realize modulation format identification (MFI), baud rate identification (BRI), chromatic dispersion identification (CDI), and optical signal-to-noise ratio (OSNR) estimation of optical signals simultaneously. This technique is based on multi-task learning (MTL) neural network model with adaptive asynchronous delay tap plot (AADTP) and asynchronous amplitude histogram (AAH) by direct detection in the intermediate nodes of optical networks. The generation of AADTP depends on the sampling rate but not the symbol rate, which makes the scheme transparent to the baud rate. The combined inputs of AADTP with AAH improve accuracies of the neural network, compared with a single input. This scheme is verified experimentally where signals with two formats, quadrature phase shift keying (QPSK) and 16 quadrature amplitude modulation (16QAM), two baud rates, 14 GBaud and 28 GBaud, and three CD situations, 0 ps/nm, 858.5 ps/nm, and 1507.9 ps/nm, are adopted. The best accuracies of MFI, BRI, CDI are 100%, 99.81%, and 99.83%, respectively. Meanwhile, the lowest average mean absolute error (MAE) of OSNR estimation is 0.2867 dB over the range of 10–24 dB (QPSK) and 15–29 dB (16QAM). It is cost-effective and practical for the proposed OPM technique to be applied in the intermediate nodes to construct smart optical networks since it uses only one photodetector assisted with an advanced deep learning algorithm.

Sparse Array Beamforming Design for Wideband Signal Models

We develop sparse array receive beamformer design methods achieving maximum signal-to-interference plus noise ratio (MaxSINR) for wideband sources and jammers. Both tapped delay line (TDL) filtering and the DFT realizations to wideband array processing are considered. The array sparsity stems from the limited number of available RF transmission chains that switch between the sensors, thereby configuring different arrays at different times. The sparse array configuration design problem is formulated as a quadratically constraint quadratic program (QCQP) and solved by using SDR (semidefinite relaxation). A computationally viable approach through SCA (successive convex relaxation) is also pursued. In order to realize an implementable design, in presence of missing autocorrelation lags, we propose parameter-free block Toeplitz matrix completion to estimate the received data correlation matrix across the entire array aperture. It is shown that the optimum wideband sparse array effectively utilizes the array aperture and provides considerable performance improvement over suboptimal array topologies.

Validation of cloud‐radio access network control unit with intra‐PHY architecture: Hardware‐in‐the‐loop framework based on frequency‐domain channel models

AbstractIn this article, a signal processing framework for hardware‐in‐the‐loop (HIL) validation of the cloud‐radio access network (C‐RAN) control unit (CU) with a crosshaul intra‐PHY architecture split is evaluated. The framework is based on the assumption that data exchanged over the crosshaul interface between the lower and higher parts of the physical layer have the form of frequency‐domain orthogonal frequency division multiplexing (OFDM) subcarriers. Therefore, it is proposed to simulate the effects of a wireless fading channel directly in the frequency domain, instead of the conventionally selected time domain. This approach leads to complexity reduction of the channel simulation model by minimizing the number of required FFT/IFFT operations, at the cost of simulation accuracy in high‐mobility and high‐delay spread scenarios. Analysis of bit error ratio (BER) and block error ratio (BLER) metrics obtained using both time‐ and frequency‐domain channel models is presented in order to validate the proposal and evaluate the accuracy loss caused by the usage of nonideal frequency‐domain models. The frequency‐domain methods are compared against the conventional wide sense stationary uncorrelated scattering (WSSUS) model implementation based on the tapped delay line (TDL). It is shown that the utilization of improved frequency‐domain models instead of the block‐fading model substantially decreases the BER/BLER prediction error in specific scenarios.

Realistic Channel Estimation of IEEE 802.11af Systems in TV White Space

This work investigates the realistic performance of IEEE 802.11af systems released for the efficient spectrum utilization of TV white space (TVWS). These systems are operated over many contiguous or non-contiguous channels based on the TVWS frequency band availability. Accordingly, we consider realistic channel estimation for TVWS system and analyze the corresponding system performance of linear minimum mean square error (LMMSE) and orthogonal matching pursuit (OMP) algorithms. While LMMSE estimates channel path gains assuming perfectly known tap delay locations, OMP estimates both channel path gains and delays. Owing to the realistic implementation and estimating the full channel state information (CSI) of sparse channels, we mainly assess the OMP performance together with the LMMSE estimation for comparison in terms of channel reconstruction and symbol detection errors. To address the channel estimation performance, Bayesian Cramer-Rao bound is derived theoretically for both perfect and imperfect CSI, and confirmed with the simulations. Simulation results demonstrate that the realistic OMP-based symbol detection performance is found to be only 1–2 dB inferior compared to the near-optimal LMMSE-based estimation with known delays in low and medium signal-to-noise-ratio regions, where communication mainly occurs in practice. In addition, the effects of channel multipath number, channel resolution and operation modes on the system performance are studied for different scenarios. The results of this work are important for the practical implementation of IEEE 802.11af-based systems.

A Step Towards the Development of Socio-cognitive Agent

The embodiment of consciousness in socio-cognitive agents play a significant role in their acceptance as co-partners. Man-machine social interaction’s success is based on the agent’s generated believable behaviors. In this regard, such an agent needs to generate realistic beliefs, intentions, goals, self-regulation, verbal, and non-verbal communication (including gestures) according to the context of ongoing interaction is very important. This study hypothesizes that the implementation of the Theory of mind (TOM) may allow the agent to change its intentions, beliefs, and desires by predicting the existing perspective and mental states of the other agents involved in the given social interaction. To study the complexity of dynamics in a social context we have taken the case study of the ‘paper-scissor-rock’ game and developed a cognitive agent capable of using gestures for non-verbal communication following the Theory of mind. This work is in progress and is being developed on the iCub robot simulation. We have used tapped delay line neural networks as the basis for reinforcement learning and strategic planning. This paper will report the cognitive model, neural network initial results obtained.

Measurement‐based determination of parameters for non‐stationary TDL models with reduced number of taps

This study proposes a new strategy of extracting parameters for tapped delay line (TDL) channel models from vehicle to infrastructure channel measurements. The proposed approach is based on an already existing method to derive parameters for a non-stationary model using first-order Markov chains. It will be shown that with the proposed method, the number of taps necessary to regenerate the delay spread of a channel can be significantly reduced. An approach will be discussed to evaluate the performance of the model. The feasibility of the method will be confirmed using channel sounding measurements.

A 50–112-Gb/s PAM-4 Transmitter With a Fractional-Spaced FFE in 65-nm CMOS

This article presents a 50–112-Gb/s current-mode four-level pulse amplitude modulation (PAM-4) transmitter with a two-tap fractional-spaced feed-forward equalizer (FFE). The principle analysis shows that the fractional-spaced FFE can provide an extended compensation range beyond the Nyquist frequency without amplifying noise. For the transmitter prototype implementation, the tap delay is adjusted by a coarse–fine capacitor array-based delay cell located in the quarter-rate clock path. Dynamic latches, pseudo-AND2s, and bandwidth-enhanced 4:1 multiplexers are employed to guarantee an adequate timing margin and a sufficient bandwidth for the data rate of 112 Gb/s. A linearity-optimized FFE driver is employed to overcome the current compression caused by the channel-length modulation. Fabricated in a 65-nm CMOS process, the measurement results show that the proposed fractional-spaced FFE can significantly improve the eye-opening in terms of expanding the eye width and optimizing the eyelid thickness. The PAM-4 transmitter can operate in both full-rate PAM-4 and half-rate NRZ modes, achieving a maximum data rate of 112 Gb/s with an energy efficiency of 2.17 pJ/bit.

Accurate method for the recognition of modulation format and transmission bit rate based on asynchronous delay tap plots

In this paper, a new method for the modulation format and bit rate recognition (MFR) is proposed. The method analyzes the asynchronously sampled signal data and uses the tools such as asynchronous delay tap plots (ADTP), principal component analysis (PCA), artificial neural network (ANN) and supported vector machine (SVM) to distinguish the different modulation format and bit rate. The mixed algorithm is able to provide accurate MFR for unprecedented number of signal modulation formats/bit rates. An example is demonstrated to recognize 18 different modulate formats/bit rates with higher than 96.17% accuracy. Such recognition performance is beyond the existing methods.