Cancellation Method Research Articles

Interference Cancellation in Wireless Communications: Past, Present, and Future

The advent of electronic communication has revolutionized the exchange of information with a plethora of services such as military, security, entertainment, and of course, telecommunications. Over the several decades, wireless communication has evolved from enabling voice calls to sending text messages, images, videos, and high-definition video conferencing to high-end applications of wireless cognition, augmented reality, and autonomous driving. However, the coexistence of many users and services in a limited spectrum may cause interference among each other. The problem of signal interference has been associated with communication systems since the beginning and has evolved with the evolution of wireless communications. In this tutorial article, we present the evolution of communication systems for the interference problem considering the cancelation methods developed in the past, an overview of the current scenario, and anticipation of future technologies.

Design of voltage and current controller parameters using small signal model-based pole-zero cancellation method for improved transient response in microgrids

Microgrids are supposed to provide stable power for seamless utility-grid interaction under all conditions as stated by IEEE-1547 standard. But, the use of power electronic inverter makes the microgrid sensitive to transients than synchronous generator-based plants. This degrades the voltage/frequency responses during transients, which can lead to transient stability problem if not controlled properly. Hence, the design of effective closed-loop voltage and current (V/I) controllers is highly desired to control the inverter output against the disturbances. The V/I controllers are based on PI (proportional-cum-integral) formulas. Thus, the effectiveness of V/I controllers relies on how accurate that their gain parameters are tuned. Many PI-tuning methods have been developed in the literature, but, it is yet difficult to identify a suitable method for an application. Also, only a few researchers have focused on the microgrids due to the complexity involved in its controller design by the presence of V/I cascaded dual-loop. Hence, to address this problem, this paper proposes a novel way of designing V/I controller parameters by using pole-zero cancellation method. This method is implemented by deriving the microgrid’s small-signal model. This improves the transient response through reduced system order and/or alleviated sluggish/marginal-stable/unstable poles by adding zeros at same places where those poles are laid, to in effect cancel them. The efficacy of the proposed method over existing methods is assessed by plotting frequency and voltage responses under different test conditions. From the simulation results, it is witnessed that the proposed method relatively improved the transient characteristics of microgrids.Article HighlightsAnalyzes the applicability of conventional PI tuning methods for microgrid controllers’ design.Proposes a novel small signal model based pole-zero cancellation method for the design of microgrid controllers.Enhances the gain margin, which improves the stabilization capacity of the system when subjected to disturbances.Improves the transient behavior of frequency and voltage responses, which ensure the safety of sensitive loads.

Pulse rate estimation from forehead photoplethysmograph signal using RLS adaptive filtering with dynamical reference signal

Objective: Pulse rate (PR) extracted from Photoplethysmograph (PPG) is a significant feature in emotion recognition. However, PPG signal can be easily affected by the motion artifacts (MA) produced from the body movement and the random head swing of the subjects who are in Immersive Virtual Environments (IVE). The objective is to estimate PR from MA corrupted PPG signal.Methods: In order to reduce the influence of random MA, we propose a novel adaptive noise cancellation (ANC) method. This method could attenuate MA and reduce the execution time by adopting RLS adaptive filtering with dynamical reference signal (DRS-RLS). Then the spectral peak tracking with verification based on the Fast Fourier Transform (FFT) method is used to estimate PR value.Results: In this paper, the two-channel PPG signals and tri-axis acceleration signals were recorded synchronously from forehead by the virtual reality (VR) physiological helmet platform developed in our research center. Seventeen participants were able to observe and move randomly in four IVEs. The mean average absolute error (μAAE) using our proposed PR estimation method is 2.40 beats per minute (BPM). Furthermore, verification result of the proposed method on a public database of 22 PPG recordings showed the μAAE (2.01 BPM) and runtime (17.2 ms) of each time window.Conclusion: The proposed PR estimation method has achieved the lowest error compared with RLS adaptive filtering using fixed axis as reference signal or cascade RLS adaptive filtering. And the result has also shown a lower μAAE and less runtime than other adaptive filtering methods proposed in recent years.Significance: The proposed method in this paper has potential to be implemented in wearable devices due to its low error and low computation cost. It also provides a new way for reference signal selection of adaptive filtering.

Optimizing the strength of the Bourdon effect by varying the triangle arrangement.

The Bourdon illusion refers to the perceived bentness of the straight collinear edges when two right-angled triangles are placed apex to apex. We studied this illusion using a cancellation method. In the first of three experiments, we manipulated the apex angle, with six different angles ranging from 4° to 45°. Results indicated that the Bourdon illusion is strongest when the angle is around 12°. In the second experiment, we compared four scalene triangles with a right-angled triangle. The angular shift was most salient when the shape corresponded to a right-angled triangle. In the third experiment, the patterns were created by varying the size of one right-angled triangle while holding the size of the second right-angled triangle constant. Results indicated that the Bourdon illusion was strongest when both right-angled triangles were of equal size. Our data suggest that the Bourdon illusion depends critically upon the specific arrangement of shapes in the display.

A customized scheme of crosstalk cancellation for operational transfer path analysis and experimental validation

To overcome crosstalk effects in operational transfer path analysis (OTPA) for effective identification and evaluation of vibration transfer path contributions based on measured response signals, a customized scheme of crosstalk cancellation for OTPA is proposed in this paper, which flexibly adopts different crosstalk cancellation methods for different path stages, and quantitatively evaluates transfer path contributions with high accuracy and efficiency. Firstly, the fundamental theories of OTPA and two crosstalk cancellation methods, prior transmissibility function-based method and independent component analysis (ICA) based method, are introduced. Secondly, an OTPA model is constructed for the test bed with shell structures, and the effects of airborne path contributions on OTPA is also analysed. Thirdly, the proposed customized scheme is applied to the two-stage transfer path of the test bed, and the vibration path contributions are comprehensively evaluated and analysed. Generally, this study proposes a flexible crosstalk cancellation scheme of OTPA for complex mechanical systems, which can provide reliable evidences for vibration and noise reduction and control.

Research on the common mode suppression method of temperature noise in an NV color center spin magnetometer

In this paper, two symmetrical magnetic formants in a nitrogen-vacancy (NV) ensemble are used to detect the two symmetrical spin states independently by means of microwave modulation and demodulation and frequency locking. Through the method of differential common mode cancellation, the spin information noise caused by temperature can be suppressed, and the measurement sensitivity of the NV magnetometer can be improved. In the experiment, a double formant magnetic detection system is built. By giving the same feedback to two symmetrical magnetic formants, we achieve differential common mode cancellation. From the experimental results, the temperature noise is reduced by 10 times, and the magnetic field sensitivity is increased from 126.8 pT Hz−1/2 to 13 pT Hz−1/2. The research realizes the suppression of temperature noise for the NV color center spin magnetometer, which provides technical support for improving the sensitivity and bandwidth of magnetometers.

Finite Control Set—Model Predictive Control with Non-Spread Spectrum and Reduced Switching Frequency Applied to Multi-Cell Rectifiers

Multi-cell converters are widely used in medium-voltage AC drives. This equipment is based on power cells that operate with low-voltage-rating semiconductors and require an input multipulse transformer. This transformer cancels the low-frequency current harmonics generated by the three-phase diode-based rectifier. Unfortunately, this transformer is bulky, heavy, expensive, and does not extend the existing power cell (three-phase rectifier—Direct Current (DC) voltage-link—single-phase inverter) to the transformer. In this study, a harmonic cancelation method based on finite control set-model predictive control (FCS–MPC), extending the power cell’s modularity to the input transformer. On the other hand, it considers treating the two disadvantages of the FCS–MPC: High switching frequency and spread spectrum. The details were developed in theory and practice to obtain satisfactory experimental results.

Robust Vibration Control Based on Rigid-Body State Observer for Modular Joints

The vibration caused by resonance modes frequently occurs during acceleration and deceleration of the modular joint integrated with flexible harmonic drive. The conventional equivalent rigid-body velocity method with observer can suppress the residual vibration induced by resonant frequency but has poor robustness to model uncertainties and external disturbances. Moreover, it cannot eliminate the torque ripple caused by the harmonic drive during low-speed uniform motion, reducing the velocity tracking accuracy. Hence, a velocity controller with a rigid-body state observer and an adjustable damper is designed to improve the robust performance and velocity tracking accuracy. The designed rigid-body state observer allows a higher gain so that the bandwidth of the observer can increase, and the equivalent rigid-body velocity can be acquired more accurately. Notably, the high gain observer reduces the sensitivity to model uncertainties and exotic disturbances, especially near the resonant frequency. In addition, the observer combined with an adjustable damper can suppress the residual vibration and torque ripple simultaneously. The proposed method is compared experimentally with a PI method and two other rigid-body velocity methods, such as the conventional equivalent rigid-body observer method and the self-resonance cancellation method, to verify its advantages.

Robust Hybrid Precoding/Combining Designs for Full-Duplex Millimeter Wave Relay Systems

In this article, we propose hybrid precoding/combining designs for full-duplex amplify-and-forward millimeter wave relay systems. The imperfect channel estimations induced by applicable estimation techniques are considered to develop robust fully digital transceivers. A zero-space self-interference (SI) cancellation method is proposed to attenuate the SI. An alternating method with closed-form solutions is utilized to solve the hybrid processors. Simulation results show that the proposed design is close to the fully digital solutions and prevails the existing designs.

Optimal resource cost for error mitigation

One of the central problems for near-term quantum devices is to understand their ultimate potential and limitations. We address this problem in terms of quantum error mitigation by introducing a framework taking into account the full expressibility of near-term devices, in which the optimal resource cost for the probabilistic error cancellation method can be formalized. We provide a general methodology for evaluating the optimal cost by connecting it to a resource-theoretic quantifier defined with respect to the noisy operations that devices can implement. We employ our methods to estimate the optimal cost in mitigating a general class of noise, where we obtain an achievable cost that has a generic advantage over previous evaluations, as well as a fundamental lower bound applicable to a broad class of noisy implementable operations. We improve our bounds for several noise models, where we give the exact optimal costs for the depolarizing and dephasing noise, precisely characterizing the overhead cost while offering an operational meaning to the resource measure in terms of error mitigation. Our result particularly implies that the heuristic approach presented by Temme et al. [K. Temme, S. Bravyi, and J. M. Gambetta, Phys. Rev. Lett. 119, 180509 (2017)] is optimal even in our extended framework, putting fundamental limitations on the advantage provided by the extra degrees of freedom inherent in near-term devices for this noise model.

A Fragmentation-Based Graph Embedding Framework for QM/ML.

We introduce a new fragmentation-based molecular representation framework "FragGraph" for QM/ML methods involving embedding fragment-wise fingerprints onto molecular graphs. Our model is specifically designed for delta machine learning (Δ-ML) with the central goal of correcting the deficiencies of approximate methods such as DFT to achieve high accuracy. Our framework is based on a judicious combination of ideas from fragmentation, error cancellation, and a state-of-the-art deep learning architecture. Broadly, we develop a general graph-network framework for molecular machine learning by incorporating the inherent advantages prebuilt into error cancellation methods such as the generalized Connectivity-Based Hierarchy. More specifically, we develop a QM/ML representation through a fragmentation-based attributed graph representation encoded with fragment-wise molecular fingerprints. The utility of our representation is demonstrated through a graph network fingerprint encoder in which a global fingerprint is generated through message passing of local neighborhoods of fragment-wise fingerprints, effectively augmenting standard fingerprints to also include the inbuilt molecular graph structure. On the 130k-GDB9 dataset, our method predicts an out-of-sample mean absolute error significantly lower than 1 kJ/mol compared to target G4(MP2) calculated energies, rivaling current deep learning methods with reduced computational scaling.

A Low-Noise and Fast-Settling UHF RFID Receiver With Digitally Controlled Leakage Cancellation

UHF RFID reader suffers from a strong transmitter (Tx) leakage signal coupled to a receiver (Rx), especially for an area-compact single-antenna implementation. Then, several Tx leakage cancellation schemes have been developed not to saturate the Rx and to minimize the performance degradation. This brief proposes a UHF RFID reader Rx with a low noise performance and a fast settling time by employing a digitally controlled leakage cancellation method in both passive and active realizations. A digitally-controlled passive vector reflector enhances the Tx to Rx isolation ratio by providing the optimum load impedance. An active anti-leakage feedback loop adaptively tracks the time-varying leakage and generate the phase-inverted leakage replica to suppress the leakage. The prototype chip is fabricated in a CMOS 55 nm process and the area of the chip is 2.1 mm <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times1.8$ </tex-math></inline-formula> mm. The passive leakage cancellation (PLC) with a vector reflector endures the 1 dBm leakage with a low Rx noise figure of 12.5 dB and 35.7 mW power consumption. The active leakage cancellation (ALC) with an anti-leakage feedback loop covers 6 dBm leakage with a fast settling time of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4.6~\mu \text{s}$ </tex-math></inline-formula> and 58 mW power consumption.

Inter-Band Interference Cancellation Based on Complex ICA for 100Gbit/s/λ Non-Orthogonal m-CAP NGFI-II Fronthaul Data Transmission

Next generation fronthaul interface (NGFI) has been adopted as the mobile fronthaul (FH) transportation solution of the next generation (NG) mobile network, which requires high bandwidth and architecture flexibility. Spectral efficiency (SE) is a key performance indicator that worth discussion for NG mobile FH. In this paper, a novel inter-band interference (IBI) cancellation method based on complex independent component analysis (ICA) is proposed in non-orthogonal multiband CAP (NO-m-CAP) system. The interfering distortion caused by spectral overlapping between adjacent sub-bands in non-orthogonal multi-band CAP is mitigated by the proposed method, and the overall SE has been improved. As a proof of concept, an experimental demonstration of 100Gb/s/λ NGFI-II data transmission over 25km SSMF is carried out. Simple intensity modulator at central unit (CU) and a coherent detection at distributed unit (DU) are applied to achieve high-performance, low-cost and flexible mobile FH data transmission. A maximum SE improvement of 15% is obtained with the proposed method for both 4-band and 8-band assuming a 7% HD-FEC limit. Flexible data rate allocating, from 12.5Gb/s to 100Gbps with a bandwidth granularity of 12.5Gb/s, is also demonstrated.

Simulation of LMS based adaptive noise cancellation using Labview

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

Dual channel speech enhancement using particle swarm optimization

Adaptive processing for canceling noise is a powerful technology for signal processing that can completely remove background noise. In general, various adaptive filter algorithms are used, many of which can lack the stability to handle the convergence rate, the number of filter coefficient variations, and error accuracy within tolerances. Unlike traditional methods, to accomplish these desirable characteristics as well as to efficiently cancel noise, in this paper, the cancelation of noise is formulated as a problem of coefficient optimization, where the particle swarm optimization (PSO) is employed. The PSO is structured to minimize the error by using a very short segment of the corrupted speech. In contrast to the recent and conventional adaptive noise cancellation methods, the simulation results indicate that the proposed algorithm has better capability of noise cancelation. The results show great improvement in signal to noise ratio (SNR) of 96.07 dB and 124.54 dB for finite impulse response (FIR) and infinite impulse response (IIR) adaptive filters respectively.

Modified GSC Method to Reduce the Distortion of the Enhanced Speech Signal Using Cross-Correlation and Sidelobe Neutralization

The generalized sidelobe canceller (GSC) method is a common algorithm to enhance audio signals using a microphone array. Distortion of the enhanced audio signal consists of two parts: the residual acoustic noise and the distortion of the desired audio signal, which means that the desired audio signal is damaged. This paper proposes a modified GSC method to reduce both kinds of distortion when the desired audio signal is a non-stationary speech signal. First, the cross-correlation coefficient between the canceling signal and the error signal of the least mean square (LMS) algorithm was added to the adaptive process of the GSC method to reduce the distortion of the enhanced signal while the energy of the desired signal frame was increased suddenly. The sidelobe pattern of beamforming was then presented to estimate the noise signal in the beamforming output signal of the GSC method. The noise component of the beamforming output signal was decreased by subtracting the estimated noise signal to improve the denoising performance of the GSC method. Finally, the GSC-SN-MCC method was proposed by merging the above two methods. The experiment was performed in an anechoic chamber to validate the proposed method in various SNR conditions. Furthermore, the simulated calculation with inaccurate noise directions was conducted based on the experiment data to inspect the robustness of the proposed method to the error of the estimated noise direction. The experiment data and calculation results indicated that the proposed method could reduce the distortion effectively under various SNR conditions and would not cause more distortion if the estimated noise direction is far from the actual noise direction.

A Dual-Mode InGaP/GaAs HBT Power Amplifier Using a Low-Loss Parallel Power-Combining Transformer with IMD3 Cancellation Method

A dual mode InGaP/GaAs heterojunction bipolar transistor (HBT) power amplifier (PA) using a parallel power-combining transformer (PCT) is presented herein. A low loss transformer is implemented on a printed circuit board (PCB) to improve the passive efficiency of a PCT. Dual-mode operation is applied to reduce the current consumption at a low power level. In the low-power (LP) mode, one of the individual amplifiers is turned off to reduce the current consumption. Additionally, a third-order intermodulation distortion (IMD3) cancellation method using a PCT combiner is proposed to improve linearity performance. Nonlinear IMD3 components from each amplifier cancel each other out through magnetic coupling in the secondary winding of the PCT. The implemented PA achieves a saturated output power of 33.8 dBm and a peak power-added efficiency (PAE) of 54.5% at 0.91 GHz with a 5-V power supply. An average output power of 25.2 dBm with an adjacent channel leakage ratio (ACLR) of −42 dBc is delivered when the PA is tested with an orthogonal frequency division multiplexing (OFDM) 64-quadrature amplitude modulated (64-QAM) signal with a bandwidth of 10 MHz and peak-to-average power ratio (PAPR) of 7.8 dB. When compared with the high-power (HP) mode operation, the LP mode operation could save 48% of the current consumption at an average output power of 10.4 dBm.

Broadband cancellation method in an adaptive co-site interference cancellation system

With the boom of communication systems on independent platforms (such as, airplanes and vessels), co-site interference has become prominent. Currently, extensive research has been conducted on the development of an adaptive co-site interference cancellation system (ACICS); however, the related interference cancellation bandwidth characteristics have not been adequately investigated, thereby critically restricting the further optimisation of the ACICS design. In this study, the bandwidth signal calculation formula of the ACICS interference cancellation ratio is derived, and the quantitative relationships among the interference cancellation bandwidth, interference cancellation ratio, system gain, and delay-matching degree are analysed exhaustively. The results reveal that the higher the required interference cancellation ratio, the smaller is the interference cancellation bandwidth; the interference cancellation bandwidth can be enhanced to a limited degree by increasing the system gain. Furthermore, the interference cancellation bandwidth and the delay-matching distance follow an approximately inverse relation, and the interference cancellation bandwidth can be improved by delay matching. The nearest matching method can be employed for broadband interference. Finally, the conducted simulations and experiments validate the correctness and effectiveness of the theoretical analysis.

A continuous phase-frequency modulation technique and adaptive pump noise cancellation method of continuous-wave signal over mud telemetry channel

Continuous wave telemetry is one of the critical downhole-to-surface transmission techniques of downhole information for logging while drilling (LWD). This paper aims to present a highly effective modulation technique for a continuous wave telemetry called Continuous Phase-Frequency Keying (CPFK) and an adaptive coherent detection method for the CPFK signal. The modulation equation of the CPFK signal is established according to the acceleration/deceleration time of the motor in a continuous wave generator, the coherent detection method is given for the demodulation of CPFK signal, and then the adaptive mud pump noise cancellation algorithm is proposed for identifying CPFK signals based on probability analysis and PSO (Particle Swarm Optimization) algorithm. The results of simulation analysis show that the proposed CPFK modulation mode is feasible and the adaptive mud pump noise cancellation algorithm can realize the demodulation and decoding of CPFK signals. It has been found from the analysis that pump noise is the main noise affecting the demodulation of CPFK signals, accurate removal of pump noise can effectively improve the frequency band utilization of CPFK signal and reduce the bit error probability of the adaptive mud pump noise cancellation algorithm.

Application of powerline noise cancellation method in correlation identification of controlled source electromagnetic method

Abstract Powerline interference in the controlled source electromagnetic method has traditionally been one of the biggest conundrums plaguing geophysicists, and its conventional denoising methods primarily include filtering and noise estimation. The filter method leaches noise at specific frequency points, which might also filter useful signals; the noise estimation method significantly eliminates interference, whereas the premise is that the noise is stable after a short time and a recorder is necessary in the field. In the present study, using the periodicity and symmetry of powerline noise, we propose a subtraction and an addition method for cancellation of the powerline noise. First, the transmitted signal is optimized so that the equivalent transmitted signal is an m sequence; then the response signal is processed by using the cancellation method; subsequently, the correlation identification is applied and finally, we solve the earth impulse response by means of the Wiener filter deconvolution method. Simulation experiments and field data tests demonstrate that the powerline noise can be well suppressed by the cancellation method proposed in the present study, so that the system identification accuracy is greatly improved. The method is simple in principle and effective in removing powerline noise, which presents a novel perspective on noise elimination for system identification.