In-phase Quadrature Research Articles

Blind Estimation of GPS M-Code Signals under Noncooperative Conditions

In the process of Global Positioning System (GPS) modernization, M-code signals with better immunity to interference have been proposed and used in place of P(Y) signals as new authorization signals. A typical positioning, navigation, and timing (PNT) service is based on the local interrelation operation between the reference signal and the received signal. To obtain a PNT, the receiver should generate replicas of the pseudorandom code for acquisition and tracking. However, due to the use of an encryption algorithm, the receiver cannot use the M-code signal under noncooperative conditions. This paper presents an algorithm for estimating M-code sequences without prior knowledge. This algorithm adopts a waveform matching technique and a time domain filtering method to extract M-code from the in-phase channel and quadrature channel of the GPS L1 band. A high-gain antenna is used to receive GPS signals to keep the signal from being drowned out by noise. The experimental results show the feasibility of the method. Therefore, it is helpful for studying and evaluating the performance achieved without prior knowledge of the GPS signals.

Global Estimation and Compensation of Linear Effects in Coherent Optical Systems Based on Nonlinear Least Squares

This article proposes a new estimation and compensation approach to mitigate several linear and widely linear effects in coherent optical systems using digital signal processing (DSP) algorithms. Compared to most of the available strategies that employ local estimation and/or compensation algorithms, this approach performs a global impairments estimation and compensation based on nonlinear least squares. The proposed method estimates and compensates for the chromatic dispersion (CD), carrier frequency offset (CFO), in-phase/quadrature (IQ) imbalance, and laser phase noise in two steps. First, it estimates the quasi-static parameters related to the CD, CFO, and both transmitter and receiver IQ imbalance. Second, it estimates both transmitter and receiver lasers’ phases and compensates for all the imperfections by using a zero-forcing equalizer. Simulations show the effectiveness of the approach in terms of statistical performance and computational time. The estimation performance is assessed by computing the Cramér–Rao lower bound, while the detection performance is compared to a modified clairvoyant equalizer.

Delta-Sigma Modulator-Embedded Digital Predistortion for 5G Transmitter Linearization

This article presents two novel digital predistortion (DPD) based architectures that jointly mitigate the inphase/quadrature (IQ) modulator impairments and the power amplifier (PA) nonlinear distortion in wireless transmitters. The proposed architectures are multibit cartesian and complex delta-sigma modulator-based joint DPDs, called CDSM-JDPD and CXDSM-JDPD, respectively, which enable using low-cost digital-to-analog converters (DACs) while offering versatile linearization capabilities to combat the coexisting distortions of the PA and the IQ modulator. The proposed approach alleviates the need for reverse modeling and implementation of extra hardware to separately deal with frequency-dependent IQ impairments. Moreover, the CXDSM-JDPD enhances the linearization performance and relaxes the high oversampling ratio (OSR) requirement by quantizing the signal more efficiently. Furthermore, the presented concepts inherently support the use of low-resolution DACs, which offers a tremendous advantage in designing and implementing low-cost and energy-efficient radio transmitters. Extensive set of hardware-in-the-loop RF verification measurements with a commercial PA are provided, including two timely 5G New Radio (NR) scenarios at NR bands n3 and n78, while covering channel bandwidths up to 100 MHz and varying the OSR and the DAC bit resolution. The obtained results demonstrate the excellent linearization capabilities of the proposed solutions and their superiority compared to other DSM-based DPD approaches.

Low-complexity and blind receiver in-phase/quadrature imbalances compensation and estimation in the frequency domain for high-order modulation formats.

A frequency domain (FD) 4×2 multi-input and multi-output (MIMO) equalizer based on radially directed equalizer is proposed to compensate receiver in-phase/quadrature (IQ) imbalances of M-ary quadrature amplitude modulation signals. This algorithm has a significantly lower complexity compared with a conventional time-domain 4×2 MIMO equalizer. Furthermore, each of imperfection estimations is derived from the converged discrete frequency response of the FD 4×2 MIMO equalizer. The simulation and experimental results indicated that the receiver (Rx) IQ imbalances were fully compensated by the proposed equalizer and precisely estimated by estimators, even for long-haul transmission with Rx IQ imbalances varying over a wide range.

Thin-film lithium niobate dual-polarization IQ modulator on a silicon substrate for single-carrier 1.6 Tb/s transmission

We successfully demonstrate a monolithic integrated dual-polarization in-phase/quadrature (IQ) modulator based on thin-film lithium niobate platform with a silicon substrate, which consists of IQ modulators, spot-size converters, and a polarization rotator combiner. When coupled with polarization maintaining fibers, the measured insertion loss of the modulator is 12 dB. In addition, we experimentally achieve a single-carrier 1.6 Tb/s net bitrate transmission.

Feedforward Neural Network-Based EVM Estimation: Impairment Tolerance in Coherent Optical Systems

Error vector magnitude (EVM) is commonly used for evaluating the quality of m-ary quadrature amplitude modulation (mQAM) signals. Recently proposed deep learning techniques for EVM estimation extend the functionality of conventional optical performance monitoring (OPM). In this article, we evaluate the tolerance of our developed EVM estimation scheme against various impairments in coherent optical systems. In particular, we analyze the signal quality monitoring capabilities in the presence of residual in-phase/quadrature (IQ) imbalance, fiber nonlinearity, and laser phase noise. We use feedforward neural networks (FFNNs) to extract the EVM information from amplitude histograms of 100 symbols per IQ cluster signal sequence captured before carrier phase recovery. We perform simulations of the considered impairments, along with an experimental investigation of the impact of laser phase noise. To investigate the tolerance of the EVM estimation scheme to each impairment type, we compare the accuracy for three training methods: 1) training without impairment, 2) training one model for all impairments, and 3) training an independent model for each impairment. Results indicate a good generalization of the proposed EVM estimation scheme, thus providing a valuable reference for developing next-generation intelligent OPM systems.

Large Dynamic Range in Acoustic Detection Realized by a Dual-Diaphragm Based Sensing System With IQ-PGC Phase Demodulation

A dual-diaphragm based acoustic sensing system has been proposed to increase the dynamic range by using a thin diaphragm (70 nm) of gold diaphragm to decrease minimum detectable acoustic pressure and a thick one (300 nm) to increase maximum detectable acoustic pressure. Signals from the two diaphragms are synchronously demodulated using frequency division multiplexing (FDM) combined with an in-phase/quadrature (IQ) and a phase generated carrier (PGC) phase demodulation. Signal crosstalk from the two diaphragms is avoided by adding a carrier modulation frequency shift to one of them. The underwater sensing performance of the system is tested under the acoustic signals ranging from 100 to 1500 Hz. Experimental results demonstrate that the average dynamic range reaches 98.4 dB in 300 ~ 1500 Hz, which is obviously improved comparing to the sensor barely using a 70 nm diaphragm (81.2 dB) or a 300 nm one (74.2 dB). In addition, the sensor performs high and flat sensitivity under low acoustic pressure (less than 110 Pa) with an average phase sensitivity of −164.2±2.6 dB re 1 rad/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> Pa. Due to the characteristic of large dynamic range and compact size, the proposed sensing system is believed to have potential application prospects in acoustic detection area.

A 220 GHz Orthogonal Modulator Based on Subharmonic Mixers Using Anti‐Paralleled Schottky Diodes

In this paper, A 220 GHz orthogonal modulator based on two symmetrical subharmonic mixers is designed, analyzed and measured, where the mixers are implemented basde on antiparallel Schottky diodes. The orthogonal modulator consists of a 90° phase shifted 220 GHz 3 dB coupler, two sub-harmonically pumped mixers and an in-phase 110 GHz 3 dB power divider. The IF output signals are in-phase (I) branch and quadrature (Q) branch operating from DC±3.5GHz. In the back to back experimentaltests, it is shown that the conversion loss of the two 220 GHz I/Q mixers is less than 30 dB when the IF operating frequency is DC−3.5 GHz, IF input power is −10 dBm and the LO power is around 6 mW. Based on floating-point simulation, the amplitude and phase imbalance of the I/Q mixer are less than 0.2 dB and 2 degree respectively. When the 220 GHz modulator and demodulator are set in a back to back configuration, a signal-to-noise ratio of 21 dB can be obtained using the 16QAM modulation type.

Online Compensation of Phase Delay Error Based on P-F Characteristic for MEMS Vibratory Gyroscopes.

In this paper, an online compensation method of phase delay error based on a Phase-Frequency (P-F) characteristic has been proposed for MEMS Coriolis Vibratory Gyroscopes (CVGs). At first, the influences of phase delay were investigated in the drive and sense mode. The frequency response was acquired in the digital control system by collecting the demodulation value of drive displacement, which verified the existence and influence of the phase delay. In addition, based on the P-F characteristic, that is, when the phase shift of the nonresonant drive force through the resonator is almost 0° or 180°, the phase delay of the gyroscope is measured online by injecting a nonresonant reference signal into the drive-mode dynamics. After that, the phase delay is self-corrected by adjusting the demodulation phase angle without affecting the normal operation of the gyroscopes. The approach was validated with an MEMS dual-mass vibratory gyroscope under double-loop force-to-rebalance (in-phase FTR and quadrature FTR) closed-loop detection mode and implemented with FPGA. The measurement results showed that this scheme can detect and compensate phase delay to effectively eliminate the effect of the quadrature error. This technique reduces the zero rate output (ZRO) from −0.71°/s to −0.21°/s and bias stability (BS) from 23.30°/h to 4.49°/h, respectively. The temperature sensitivity of bias output from −20 °C to 40 °C has reached 0.003 °/s/°C.

Experiment and simulation of microwave detection using IQ demodulation method for breast tumor screening

Breast cancer has become the most diagnosed cancer in the world. Microwave detection the breast tumor is attractive due to its high dielectric property contrast between different tissues of tumor. In this paper, we proposed an In-phase-Quadrature (IQ) demodulation-based method to detect the breast tumor with microwave at a frequency of 1.3 GHz. The microwave detection system consists of two signal generators, 12 transmitting/receiving antennas, two talent switches, a phantom and an IQ-Mixer. The amplitude information at the receiving antennas can be obtained by analyzing the difference frequency signals generated with two microwave signal generators. We also use the finite-difference time-domain (FDTD) method for simulation verification, which can simulate the propagation of the electromagnetic wave. Through experiments and simulations of microwave hardware system and FDTD method, it can be proved that the results are consistent. The experimental and simulation results show that when the tumor phantom diameter decreases or its depth from the receiving antenna increases, whether there is a tumor phantom can be clearly distinguished. Moreover, we also explore the effects of different tumor phantom locations on the receiving antennas. The results show that it is feasible to detect the breast tumor with the IQ demodulation method based on microwave.

A Parametric Network for the Global Compensation of Physical Layer Linear Impairments in Coherent Optical Communications

This paper proposes a parametric network for the joint compensation of multiple linear impairments in coherent optical communication systems. The considered linear impairments include both static and time-variant effects such as in-phase/quadrature (IQ) imbalance, laser phase noise (PN), chromatic dispersion (CD), polarization mode dispersion (PMD), and carrier frequency offset (CFO). To jointly compensate for these considered impairments, the proposed network is composed of parametric layers that exploit the particular signal model of each impairment. The layers&#x2019; parameters are jointly learned during a training stage. This stage uses a supervised step that exploits the knowledge of some transmitted data (preamble and/or pilots) and a self-labeling step that uses the knowledge of the symbol constellation. In addition, a new validation technique that does not require a different dataset is developed to avoid overfitting. The parametric network performance is compared to classical digital signal processing (DSP), and Deep Learning (DL) approaches using simulated data. Simulation results show that the proposed network outperforms the competing approaches in terms of Bit Error Rate (BER) while maintaining a relatively reduced computational complexity. In the scenarios considered, compared to the parametric network, the DSP approach introduces an OSNR penalty between 0.2 dB and 1.7 dB at a BER of 4&#x00D7;10-3. Furthermore, simulation results demonstrate that the proposed network is way more flexible than other approaches since it can easily be adapted to a different scenario and coupled with other techniques.

Three-Phase Flow Tomography System in Upward-Vertical High-Viscous-Oil/Water/Gas Flow

A new three-phase flow tomography system is presented in this work. The system was developed to be applied in high-viscous-oil/water/gas flow arranged in different flow patterns, with the three fluids present simultaneously in a crossing point. The primary measurement is based on a simpler and reliable digital in-phase/quadrature (IQ) demodulator and a wire-mesh sensor (WMS), but the system is capable of including different types of primary measurements. Dynamic three-phase flow tests were carried out to verify the system performance and compare its results with the ones obtained by quick-closing valves (QCVs) and a high-speed video camera. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">In situ</i> volumetric fractions and flow patterns were compared. The experiments were conducted in a vertical glass pipe of 50-mm i.d. and 12-m height. The observed three-phase flow patterns were water-continuous churn flow with dispersed bubbles and oil drops (WChBoDo), water-continuous slug flow with Taylor bubbles, spherical bubbles, and oil drops (WPiBoDo), and oil-continuous slug flow with Taylor bubbles, spherical bubbles, and water drops (OPiBoDi). Compared with the measurements using QCVs, the average relative errors of the measured volumetric phase fractions were 12% for water, 13% for air, and 22% for oil. The experimental results, including the details of the flow inside the pipe, the phase distributions, and the objective characterization of flow patterns, suggest that the proposed system is a promising option for three-phase flow-related studies and developments. The proposed technique can reach 8930 frames/s with a <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$16\times16$ </tex-math></inline-formula> WMS.

Experimental Evaluation of Sub-Sampling IQ Detection for Low-Level RF Control in Particle Accelerator Systems.

The low-level radio frequency (LLRF) control system is one of the fundamental parts of a particle accelerator, ensuring the stability of the electro-magnetic (EM) field inside the resonant cavities. It leverages on the precise measurement of the field by in-phase/quadrature (IQ) detection of an RF probe signal from the cavities, usually performed using analogue downconversion. This approach requires a local oscillator (LO) and is subject to hardware non-idealities like mixer nonlinearity and long-term temperature drifts. In this work, we experimentally evaluate IQ detection by direct sampling for the LLRF system of the Polish free electron laser (PolFEL) now under development at the National Centre for Nuclear Research (NCBJ) in Poland. We study the impact of the sampling scheme and of the clock phase noise for a 1.3-GHz input sub-sampled by a 400-MSa/s analogue-to-digital converter (ADC), estimating amplitude and phase stability below 0.01% and nearly 0.01°, respectively. The results are in line with state-of-the-art implementations, and demonstrate the feasibility of direct sampling for GHz-range LLRF systems.

Three-dimensional echo decorrelation imaging of percutaneous microwave ablation in liver tumors

In a pilot clinical study, patients underwent standard-of-care percutaneous microwave ablation (MWA) of liver tumors with monitoring by three-dimensional (3D) ultrasound echo decorrelation imaging. An MWA needle (Amica) was inserted into each tumor, guided by x-ray computed tomography (CT) and ultrasound imaging. A matrix ultrasound array (4Z1c array with Acuson SC2000 scanner, Siemens) was positioned on patients’ skin near the MWA needle insertion point. Paired sequential complex in-phase/quadrature (IQ) echo volumes (inter-frame time 5–20 ms) were acquired throughout ablation at 10–20 s intervals, then processed to form 3D echo decorrelation images. Respiratory motion was estimated and compensated using a theoretical model that separates motion- and heat-induced echo decorrelation. Volumetric B-mode images constructed from the same IQ data were rigidly registered to follow-up contrast-enhanced magnetic resonance (MR) image volumes, recorded within 4 days after MWA. Specified registration transformations were then applied to cumulative 3D echo decorrelation maps, which were compared voxel-wise to ablation zones segmented from MR images. Receiver operator characteristic (ROC) curve analysis indicated effective prediction of local ablation by motion-compensated echo decorrelation imaging. Comparison with subsequent follow-up MR images tested the ability of 3D echo decorrelation imaging to predict any incomplete treatment or recurrence of treated tumors.

3-D Super-Resolution Ultrasound Imaging for Monitoring Early Changes in Breast Cancer after Treatment with a Vascular-Disrupting Agent.

The purpose of this research project was to evaluate the use of 3-dimensional (3-D) super-resolution ultrasound (SR-US) imaging to assess any early changes in breast cancer after treatment with a vascular-disrupting agent (VDA). A Vevo 3100 ultrasound system (FUJIFILM VisualSonics Inc) equipped with an MX 201 transducer was used for image acquisition. A total of 2.5 × 107 microbubbles (MBs) were injected into the tail vein of anesthetized breast cancer-bearing mice using repeat bolus injections every 5 min. A total of 10 stacks of ultrasound images were collected as the transducer was mechanically moved across the tumor at 0.6 mm intervals yielding a 6-mm thick volume. At each tumor location, a stack contained 1 × 104 frames of ultrasound data that were acquired at 463 frames/sec and stored as in-phase/quadrature (IQ) format. After motion correction, each temporal stack of ultrasound images was processed separately for clutter signal removal, which was followed by MB localization and enumeration before generation of the final SR-US image. After reconstruction of the 3-D SR-US volume dataset, the tumor microvasculature was enhanced using a multiscale vessel enhancement filter. Vessels from the resultant microvascular network were then segmented using an adaptive thresholding method. Finally, mean microvascular density (MVD) measurements from each tumor volume were computed as a summarizing statistic. While no differences were found between baseline SR-US image-derived measures of MVD (p = 0.76), these same measurements were significantly lower at 24 h after VDA treatment (p < 0.001). Overall, 3-D SR-US imaging detected early tumor changes following treatment with a vascular-targeted drug.

Acceleration of reconstruction for compressed sensing based synthetic transmit aperture imaging by using in-phase/quadrature data

Compressed sensing-based synthetic transmit aperture (CS-STA) was previously proposed to recover the full radio-frequency (RF) channel dataset of synthetic transmit aperture (STA) from that of a smaller number of randomly apodized plane wave (PW) transmissions. In this way, the imaging frame rate (FR) and contrast are improved with maintained spatial resolution, compared with those of STA. Because CS-STA reconstruction is repeated for all receive elements and RF samples (with a high sampling frequency), the recovery of STA dataset in RF domain is time-consuming. In the meantime, a large amount of RF data needs to be transferred and stored, resulting in an increase of system complexity and required memory space. In this study, CS-STA is extended to in-phase/quadrature (IQ) domain (with lower sampling frequency) for the recovery of baseband STA IQ dataset to accelerate the CS-STA reconstruction by reducing the amount of data to be processed. More importantly, CS-STA reconstruction using IQ data is of practical importance, as clinical ultrasound systems typically record baseband IQ signal instead of RF signal. Simulations, phantom and in vivo experiments verify the feasibility of CS-STA in IQ domain for the recovery of STA dataset. More specifically, CS-STA using IQ data achieves similar image quality and appreciably improves reconstruction speed (by ∼3 times) compared with that using RF data. These findings demonstrate that IQ-domain CS-STA is capable of relieving the computational and storage burdens, which may facilitate the implementation of CS-STA in practical ultrasound systems.

Automatic modulation classification using modulation fingerprint extraction

An automatic method for classifying frequency shift keying (FSK), minimum shift keying (MSK), phase shift keying (PSK), quadrature amplitude modulation (QAM), and orthogonal frequency division multiplexing (OFDM) is proposed by simultaneously using normality test, spectral analysis, and geometrical characteristics of in-phase-quadrature (I-Q) constellation diagram. Since the extracted features are unique for each modulation, they can be considered as a fingerprint of each modulation. We show that the proposed algorithm outperforms the previously published methods in terms of signal-to-noise ratio (SNR) and success rate. For example, the success rate of the proposed method for 64-QAM modulation at SNR=11 dB is 99%. Another advantage of the proposed method is its wide SNR range; such that the probability of classification for 16-QAM at SNR=3 dB is almost 1. The proposed method also provides a database for geometrical features of I-Q constellation diagram. By comparing and correlating the data of the provided database with the estimated I-Q diagram of the received signal, the processing gain of 4 dB is obtained. Whatever can be mentioned about the preference of the proposed algorithm are low complexity, low SNR, wide range of modulation set, and enhanced recognition at higher-order modulations.

Experimental validation of CNNs versus FFNNs for time- and energy-efficient EVM estimation in coherent optical systems

Error vector magnitude (EVM) has proven to be one of the optical performance monitoring metrics providing the quantitative estimation of error statistics. However, the EVM estimation efficiency has not been fully exploited in terms of complexity and energy consumption. Therefore, in this paper, we explore two deep-learning-based EVM estimation schemes. The first scheme exploits convolutional neural networks (CNNs) to extract EVM information from images of the constellation diagram in the in-phase/quadrature (IQ) complex plane or amplitude histograms (AHs). The second scheme relies on feedforward neural networks (FFNNs) extracting features from a vectorized representation of AHs. In both cases, we use short sequences of 32 Gbaud m-ary quadrature amplitude modulation (mQAM) signals captured before or after a carrier phase recovery. The impacts of the sequence length, neural network structure, and data set representation on the EVM estimation accuracy as well as the model training time are thoroughly studied. Furthermore, we validate the performance of the proposed schemes using the experimental implementation of 28 Gbaud 64QAM signals. We achieve a mean absolute estimation error below 0.15%, with short signals consisting of only 100 symbols per IQ cluster. Considering the estimation accuracy, the implementation complexity, and the potential energy savings, the proposed CNN- and FFNN-based schemes can be used to perform time-sensitive and accurate EVM estimation for mQAM signal quality monitoring purposes.

A semi-blind method to estimate the I/Q imbalanc of THz orthogonal modulator

In terahertz communication, the direct frequency conversion structure in which orthogonal mixer is the main frequency conversion unit, makes engineers get into trouble of in-phase(I) branch and quadrature(Q) branch imbalance, carrier wave leakage, etc. These damages result in system performance tremendous degrades. We proposed a semi-blind method to estimate the I/Q imbalance of THz orthogonal modulator, based on predefined preamble and pilot symbols for quadrature amplitude modulation (QAM). In this paper, a transmitter with Y band quadrature mixer and 20Gbps base-band signal has been tested. The bandwidth of the baseband signal was 7GHz, and the modulation type was 16QAM. By this method, 7dB improvement of the system's symbol Mean Square Error (MSE) has been got. That means the proposed method can be used to eliminate the I/Q imbalance effectively.

Channel Estimation and Equalization for Terahertz Receiver With RF Impairments

The radio frequency (RF) impairments of analog devices have been regarded as an important factor degrading the performance of Terahertz (THz) communications, where in-phase/quadrature (IQ) imbalance and phase noise (PN) are the two typical RF impairments at THz transceiver. In this paper, we investigate the channel estimation (CE) and equalization for THz receiver in the presence of wideband IQ imbalance and PN, where single-carrier frequency-domain equalization is used. Since PN is inserted between channel impulse response (CIR) and wideband IQ imbalance at the receiver, the CIR and IQ imbalance cannot be treated together as an effective channel. Therefore, a novel two-stage CE method is derived to separately estimate the CIR and wideband IQ imbalance parameters, and its corresponding channel equalization method is designed to compensate both wideband IQ imbalance and PN, and equalizes the CIR. Theoretical and simulation results validate the efficiency of our proposed CE, and the proposed equalization method is shown to outperform the state-of-the-art methods.