Adaptive Cancellation Research Articles

Robust Adaptive Filtering Algorithm for Self-Interference Cancellation with Impulsive Noise

Self-interference (SI) is usually generated by the simultaneous transmission and reception in the same system, and the variable SI channel and impulsive noise make it difficult to eliminate. Therefore, this paper proposes an adaptive digital SI cancellation algorithm, which is an improved normalized sub-band adaptive filtering (NSAF) algorithm based on the sparsity of the SI channel and the arctangent cost function. The weight vector is hardly updated when the impulsive noise occurs, and the iteration error resulting from impulsive noise is significantly reduced. Another major factor affecting the performance of SI cancellation is the variable SI channel. To solve this problem, the sparsity of the SI channel is estimated with the estimation of the weight vector at each iteration, and it is used to adjust the weight vector. Then, the convergence performance and calculation complexity are analyzed theoretically. Simulation results indicate that the proposed algorithm has better performance than the referenced algorithms.

Fast and efficient acoustic feedback cancellation based on low rank approximation

In an adaptive feedback cancellation (AFC) scenario, it is essential for an algorithm to track and cancel the feedback signal as quickly as possible. We analyze typical feedback paths in hearing aids and show that they exhibit a low-rank nature. Further, to exploit this knowledge and improve the convergence and tracking performance for AFC, we propose the nearest Kronecker product decomposition based adaptive feedback canceller with prediction error method based signal pre-whitening. Detailed simulation study and comparison of computational complexity show that the proposed algorithm can provide improved convergence and tracking along with improved output speech quality over traditional AFC algorithms, at a moderate computational load.

Toward URLLC: A Full Duplex Relay System with Self-Interference Utilization or Cancellation

Ultra-reliable low-latency communication (URLLC) is one of the key use cases of 5G wireless communications to facilitate specific application scenarios with stringent latency and reliability demands, such as industrial automation and Tactile Internet. A full duplex (FD) relay with simultaneous transmission and reception in the same frequency band is an effective approach to enhance the reliability of cell-edge user terminals by significantly suppressing self-interference (SI). However, the signal processing latency at FD relay due to SI cancellation, referred to as relaying latency, takes a significant part in the end-to-end latency, and therefore should be minimized, while guaranteeing high reliability. In this article, we first present an up-to-date overview of the end-to-end latency for an FD relay system, addressing physical layer challenges. We investigate the possible solutions in the literature to achieve the goal of URLLC. The efficient solution is to allow a simple amplify-and-forward FD relay mode with low-complexity SI radio frequency and analog cancellations, and process the residual SI alongside the desired signal at the base station in an adaptive manner, rather than being cancelled at relay in the digital domain. Also, the residual SI can be utilized at the base station to enhance the reliability and degree of freedom in signal processing, not necessarily being cancelled as much as possible. The FD relay assisted system with adaptive SI utilization or cancellation enables extended network coverage, enhanced reliability, and reduced latency compared to the existing overview work.

An Improved Specific Harmonic Detection Method Based on Adaptive Cancellation Principle

When the active power filter (APF) and the tunable filter are used for specific harmonic suppression, the accurate single harmonic current detection module is one of the key links to ensure its harmonic suppression effect. An improved single harmonic detection method based on the principle of adaptive cancellation has been proposed, which does not have some of the problems of traditional algorithms, for instance the feedback error is not accurate enough, and the contradiction between tracking speed and steady-state accuracy. This method can accurately and quickly detect the harmonic amplitude and phase angle, and can be flexibly applied to the harmonic detection of three-phase and single-phase systems. Through theoretical analysis and MATLAB simulation, it is proved that the method can guarantee a higher steady-state accuracy and a faster tracking speed.

RF Canceller Tuning Acceleration Using Neural Network Machine Learning for In-Band Full-Duplex Systems

The fifth-generation wireless system framework provides the option to evaluate the performance of in-band full-duplex (IBFD) operation through flexible duplexing. The resulting self-interference, however, must be mitigated within a fraction of a symbol duration for successful communication. This paper introduces the use of neural network machine learning to accelerate the tuning of multi-tap adaptive RF cancellers. Additionally, the optimal network configurations, input data structures and training dataset densities that optimize the performance of this technique are presented. The tuning results of a prototype system using a two-tap canceller were measured over 20 and 100 MHz bandwidths centered at 2.5 GHz, and demonstrated averages of 40 dB cancellation and 6 tuning iterations. These results are compared to a survey of previously-reported adaptive cancellers, and illustrate that this novel application of machine learning to RF canceller tuning provides the fastest convergence speed to date, which can enable IBFD operation in dynamic interference environments.

Adaptive Filtering Method of MFL Signal on Rail Top Surface Defect Detection

Magnetic flux leakage (MFL) detection technology provides an effective method to conduct high-speed detection of the damage suffered by rail surface. With regard to high-speed detection, there is frequently a complex noise contained in the magnetic signal of railway leakage, which is similar to the amplitude of defect and the overlaps of frequency spectrum. In this paper, an improved adaptive filtering method is proposed to solve the problem caused by filtering the MFL signal on the rail top surface. Through the characteristics of distribution shown by defects on the top surface of the railway and those of the data collected by the rail top array sensor, this method is applied to construct a virtual channel containing almost only interference signals but no defects. Then, in combination with the adaptive filtering algorithm, the virtual channel signal is taken as the reference input of the adaptive canceller, each single channel MFL signal is taken as the original input of the adaptive canceller, and the filtered MFL signal is taken as the output. Then, the MFL signal of rail top is collected by the train at the speed of 30km / h on the manual calibration line. According to the experimental results, the noise intensity of MFL signal is reduced by up to 81.44%. In addition, the filtering method is adopted to process MFL signals with different directions and varying detection speed. As indicated by the results, the noise intensity of MFL signal is reduced by more than 74%.

Sparsity aware affine-projection-like filtering integrated with robust set membership and M-estimate approach for acoustic feedback cancellation in hearing aids

This paper introduces a new adaptive feedback cancellation technique for hearing aid employing robust upper error bound of set membership filtering in the M-estimate function and applied for affine-projection-like algorithm. Additionally a l1 norm based sparsity term is appended in the cost function which takes care of the convergence while estimating feedback path of the hearing aid exhibiting sparse characteristics. The proposed method of sparsity aware affine-projection-like robust set membership M-estimate (SAPL-RSM) filtering has been utilized for alleviating the impact of impulsive noise on the adaptation of feedback canceler’s weights. The SAPL-RSM technique is derived by minimizing a modified cost function involving M-estimate function constrained by a robust error bound and sparsity dependent penalty term with the motive of enhancing the convergence and lowering the computational expenses involved in the weight update process. The validation of the proposed method is carried out in the context of adaptive feedback cancellation in hearing aids. Simulations assess the efficacy of the proposed technique as an adaptive feedback canceler in terms of misalignment, added stable gain and sound quality deliverable at the user end.

Active Middle Ear Implant Patient Outcomes With Adaptive Feedback Canceller.

Evaluation of the audiological patient performance with an upgrade of the firmware from the fixed feedback canceller (FFC) to the adaptive feedback canceller (AFC) on an active middle ear implant. Retrospective observational nonrandomized group study. Private hospital. From March 2018 to September 2019, 15 patients implanted with an active middle ear implant, with 6 or more months of experience with a FFC system, were upgraded to an AFC algorithm. Functional gain, speech perception in silence and in noise, and sound localization capacities were examined. Feedback reduction was also analyzed. Thirteen patients were analyzed. Pure tone audiometric evaluation with FFC (mean value of 48.02 dB) compared with AFC at 1 (mean value of 49.12 dB) and 6 months (mean value of 42.75 dB) revealed no statistically significant differences (p = 0.889 and p = 0.358 respectively).In speech discrimination in silence, clinically relevant improvements were observed with AFC at 1 and 6 months, with a mean value of 41.5 and 38.3 dB, respectively (p = 0.03 and p = 0.021 correspondingly). In speech discrimination in noisy environments, we observed an improvement of the different conditions tested. No differences were found in localization capacities between FFC and AFC at the two different moments of evaluation. AFC is more effective than FFC in cancelling feedback and improving sound quality, allowing for better speech understanding in silence and in noise.

Nonorthogonal Multiple Access With Energy Harvesting-Based Alternate Relaying

For a downlink communication system, we propose a nonorthogonal multiple access scheme with two energy harvesting relays. The base station (BS) transmits the data of both near and far users simultaneously using the superposition coding technique. Two relays alternately amplify and forward the data to the far-user. Each relay can harvest wireless energy from the signals of both the BS and the other transmitting relay, so each relay can achieve more opportunities to accumulate more energy for a higher-quality cooperative relaying. The near-user performs adaptive interference cancelation to retrieve its desired data. Numerical results show that the nonorthogonal scheme greatly outperforms the orthogonal scheme in terms of throughput.

CMOS Full-Duplex Mixer-First Receiver With Adaptive Self-Interference Cancellation

A full-duplex transceiver with on-chip self-interference-cancellation (SIC) is presented. The achieved SIC is 110 dB, and it is realized in three stages: RF front-end hybrid, baseband analog, and baseband digital. An integrated hybrid is used in the RF front-end which employs an adaptive tuning impedance network (TIN) to track the antenna impedance variations, achieving over 50 dB of SIC. N-path mixer-first architecture is used for the receiver to improve the linearity and to provide out of band blocker cancellation. The self-interference is further attenuated in the analog domain using the down-converted sample of the transmit signal. The analog transmit interference canceler (TIC) receives the sampled copy of the transmitted signal of the power amplifier and offers adaptive amplitude and phase adjustment for the cancellation signal, obtaining more than 20 dB on-chip cancellation in the analog domain. The last step of SIC is realized in the digital domain using a nonlinear system with memory to cancel the remnant of self-interference and distortions, resulting in 43 dB of SIC. The front-end hybrid, mixer-first receiver, and analog TIC are implemented in a CMOS 65-nm technology. Thanks to adaptive gradient decent algorithm employed in the system, the total SIC of the hybrid and TIC is more than 70 dB, which is one of the highest cancellation values achieved on the chip. The die area is 4 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , and the fabricated chip consumes 80 mW dc power. The average transmit power is 23 dBm, and the noise figure of the receiver in the full-duplex mode is 11 dB.

A W-Band Single-Antenna FMCW Radar Transceiver With Adaptive Leakage Cancellation

This article presents a leakage cancellation architecture for single-antenna frequency-modulated continuous-wave (FMCW) radars at W-band. A shared antenna for transmitter (TX) and receiver (RX) can substantially reduce the form factor, cost, and complexity of radar modules. Due to the simultaneous operation of the TX and RX in FMCW radars, employing a shared antenna will, however, significantly increase TX-to-RX leakage, resulting in RX saturation and desensitization. Our proposed cancellation scheme employs analog feedback to confine the TX leakage right at the RX input port, and thus, relieves the ongoing RX chain from saturation. The proposed single-antenna transceiver (TRX) prototype was fabricated in 65-nm CMOS technology with a die area of 1 mm2. The output power of 2 dBm was achieved for the TX in a frequency range of 80–84 GHz. In addition, a conversion gain and noise figure of 45 and 15 dB was measured for the RX in the presence of the TX signal via a shared antenna port. TX-to-RX isolation of more than 45 dB was achieved in the operating W-band. The chip consumes 108 mW (80.5 mW for the TX and 27.5 mW for the RX) from a 1.2-V supply voltage. Moreover, the functionality of the single-antenna radar operation was verified by connecting the chip to an on -printed circuit board (PCB) $4 \times 8$ patch antenna array with a simulated gain of 15 dBi, implemented on RO3003 Rogers material. Using the single-antenna radar module as a demo system, a $40\times 50$ cm2 rectangular metallic plate was detected at a distance up to 19 m.

Adaptive Interference Cancellation Using Atomic Norm Minimization and Denoising

The rapid increase in the number of wireless devices in modern communication networks has significantly increased the number of interference sources, which severely impacts communication reliability. Adaptive interference cancellation is rapidly becoming a necessity for modern wireless networks. For interference cancellation, a digital beamformer adaptively adjusts its weight vector using an array processing algorithm. This, in turn, shapes the radiation pattern in a manner that minimizes interference power and maximizes the desired signal power. In this letter, we propose two atomic-norm-minimization-based methods to design a weight vector that can be used to cancel interference. We present numerical and experimental studies and compare with the minimum variance distortionless response beamformer, which outputs the highest possible signal-to-interference-plus-noise ratio (SINR). We show that our approach is robust to signal corruptions arising from carrier frequency offsets. Uniquely, our algorithm extracts the offset frequencies, thus enabling interference cancellation with maximum SINR.

Adaptive leakage signal cancellation algorithm in heterodyne FMCW system

To mitigate the leakage signal that obstructs the target information extraction in miniatured frequency modulated continuous wave (FMCW) radar system, an adaptive leakage signal cancellation algorithm is proposed in this paper. Without any help of the additional auxiliary path, all the processing for the intermediate frequency (IF) signal can be conducted in the digital domain. The basic principle to cancel leakage signal is to produce a cancelling signal, which has the same amplitude and anti-phase with the leakage signal. Differently, in this paper, the input phase parameter of the proposed method can be arbitrary and it can be modified by the corresponding corrected function. Besides, to acquire the phase noise in the leakage signal conveniently when generating cancelling signal, the information geometry theory is applied to transform the complex phase noise model into statistical characteristics calculation of the input signal. The effectiveness of the model and the proposed algorithm is verified by simulated results. Furthermore, a real FMCW system is designed to collect the practice echo signals. The resulting data denotes that the leakage signal in the received signal is greatly suppressed and the leakage signal power drops by −15.92 dB.

Design of a class of zero attraction based sparse adaptive feedback cancellers for assistive listening devices

Acoustic feedback is a frequently encountered problem in assistive listening devices (ALDs). Feedback paths in ALDs are typically sparse in nature and sparsity aware adaptive feedback cancellers can improve perceived audio quality under such scenarios. In an endeavour to improve the feedback canceller performance, a decorrelated polynomial zero attraction (DPZA) normalized least mean square (NLMS) feedback canceller is proposed in this paper. DPZA-NLMS algorithm is seen to have higher computational complexity. Hence, in an attempt to reduce computational complexity, a decorrelated l0-NLMS (D-l0-NLMS) and a decorrelated Versoria zero attraction NLMS (DVZA-NLMS) based feedback canceller are also proposed. Feedback canceller performance in terms of convergence and tracking performance as well as speech/audio quality and speech intelligibility is compared. In addition, computational complexity and memory requirements of the algorithms are also compared thus providing a hearing aid designer with better trade off choices between computational requirements and feedback cancellation performance.

CMOS 256-Pixel/480-Pixel Photovoltaic-Powered Subretinal Prosthetic Chips With Wide Image Dynamic Range and Bi/Four-Directional Sharing Electrodes and Their Ex Vivo Experimental Validations With Mice

CMOS photovoltaic-powered 256-pixel/480-pixel implantable chips with a wide image dynamic range and shared electrodes are proposed and fabricated in CIS technology for subretinal prostheses. The infra-red (IR) light is incident only on photovoltaic cells of the chip whereas the visible light is mainly incident on pixels. The proposed adaptive background cancellation circuit (ABCC) is adopted to increase the image dynamic range so that the subretinal chips can adapt for different surrounding illuminances. A two-dimensional equivalent electrode model for electric crosstalk simulation is proposed to analyze the crosstalk charges and enable the stimulation pattern design with minimum crosstalk for both chips. Moreover, the bi-directional sharing electrodes (BDSEs) are used in the 256-pixel chip to increase electrode size under the same chip area and boost the stimulation charges to 11.4 nC. The four-directional sharing electrodes (FDSEs) are used to share the electrodes in both vertical and horizontal directions and achieve 480 pixels with nearly the same electrode size under the same pixel array area. The maximum stimulation charge is 9.8 nC. The dynamic range of image light is increased to 31.65 dB (24.9 dB) in the fabricated 256-pixel (480-pixel) chip. The functions of the chip have been successfully validated by both electrical measurement and ex vivo patch clamp experiments with the retinas of mice.

Control scheme of adaptive feedforward cancellation considering of Bode’s integral theorem for synchronous vibration suppression in rotating machineries

Synchronous vibration is a major obstacle to the stable operation of rotating machineries. In previous studies, active control methods were developed to compensate for synchronous vibration using actuators, such as an active magnetic bearing or a piezo actuator. Adaptive feedforward cancellation is another well-known control method and is used to compensate for the synchronous vibration in the actual system. The control methods can compensate for the synchronous vibration; however, the amplitude of the vibration in other frequency ranges can be increased by the waterbed effect due to Bode’s integral theorem. Therefore, there is a trade-off between the compensation of the synchronous vibration and the negative impact of other vibration. In this article, a novel control scheme for the adaptive feedforward cancellation is proposed to eliminate the negative impact due to the waterbed effect. The proposed method controlled the input signal of the adaptive algorithm in the adaptive feedforward cancellation and realized an ideal feedforward controller worked independently from the feedback loop. The effectiveness of this method was verified experimentally using a test rig.

An Adaptive Offset Cancellation Scheme and Shared-Summer Adaptive DFE for 0.068 pJ/b/dB 1.62-to-10 Gb/s Low-Power Receiver in 40 nm CMOS

This brief presents the design of a low-power receiver (RX) with an adaptive equalizer and an offset cancellation scheme. The proposed adaptive offset cancellation (AOC) engine removes the random DC offset of the data path by examining the sampled data and edge outputs of a random data stream. In addition, a shared-summer decision-feedback equalizer in a half-rate structure is incorporated to reduce power dissipation and hardware complexity of the adaptive equalizer. A prototype chip fabricated in 40 nm CMOS technology occupies an active area of 0.083 mm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> . Thanks to the AOC engine, the proposed RX achieves the BER of less than 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-12</sup> in a wide range of data rates: 1.62-10 Gb/s. The proposed RX consumes 18.6 mW at 10 Gb/s over a channel with 27-dB loss at 5 GHz, exhibiting a figure-of-merit of 0.068 pJ/b/dB.

Impact of wideband interference coupling path dispersion on performance of radio‐frequency interference adaptive cancellation system

As the interference bandwidth increases, the impact of interference coupling path dispersion on the cancellation performance can no longer be ignored in open space. Especially for the radio frequency interference adaptive cancellation system (RFIACS), the impact will be more serious. In response to this problem, this study establishes the time-domain model of a wideband RFIACS considering interference coupling path dispersion characteristics, and analyses the stability, convergence speed, interference cancellation ratio (ICR), and cancellation bandwidth of RFIACS considering dispersion characteristics. And the authors define the speed factor to characterise the convergence speed. The analysis shows that the dispersion of the interference coupling path will not affect the stability of the system, but will reduce the convergence speed and ICR. The larger the interference coupling path dispersion, the lower the convergence speed, and the larger the cancellation bandwidth, the lower the ICR. The experimental results verify the theoretical analysis.

Bias-Compensated Sparsity-Aware NLMM Algorithms for Robust Adaptive Echo Cancellation

For adaptive echo cancellation in hands-free communication systems, a family of bias-compensated sparsity-aware normalized least mean M-estimate (NLMM) algorithms is proposed that are robust to both impulsive noise and noisy inputs. First, we define a new cost function that integrates the M-estimate function of the a posteriori error, the Riemannian distance between the current and previous weight vectors, and the $L_{0}$ norm of the weighted current weight vector. By minimizing the defined cost function, we develop the sparsity-aware NLMM algorithms to achieve robustness against the impulsive noise. Then, an improved cost function is developed and proved to be unbiased in the presence of input noise. This leads to the development of the bias-compensated sparsity-aware NLMM algorithms that can deal with noisy inputs. The stability and computational complexity of the proposed algorithms are analyzed as well. Experimental results for system identification and adaptive echo cancellation demonstrate that the proposed algorithms outperform the existing ones in terms of convergence rate and steady-state misalignment.

A Single-Chip Bidirectional Neural Interface With High-Voltage Stimulation and Adaptive Artifact Cancellation in Standard CMOS

A single-chip, bidirectional brain–computer interface (BBCI) enables neuromodulation through simultaneous neural recording and stimulation. This article presents a prototype BBCI application-specified integrated circuit (ASIC) consisting of a 64-channel time-multiplexed recording front-end, an area-optimized four-channel high-voltage compliant stimulator, and electronics to support the concurrent multi-channel stimulus artifact cancellation. Stimulator power generation is integrated on a chip, providing ±11-V compliance from low-voltage supplies with a resonant charge pump. High-frequency (~3 GHz) self-resonant clocking is used to reduce the pumping capacitor area while suppressing the associated switching losses. A 32-tap least mean square (LMS)-based digital adaptive filter achieves 60-dB artifact suppression, enabling simultaneous neural stimulation and recording. The entire chip occupies 4 mm2 in a 65-nm low power (LP) process and is powered by 2.5-/1.2-V supplies, dissipating $205~\mu \text{W}$ in recording and $142~\mu \text{W}$ in the stimulation and cancellation back-ends. The stimulation output drivers achieve 31% dc–dc efficiency at a maximum output power of 24 mW.