Off-Grid Compressed Channel Estimation with Parallel Interference Cancellation for Millimeter Wave Massive MIMO

Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths.

A deep multimodal fusion and multitasking trajectory prediction model for typhoon trajectory prediction to reduce flight scheduling cancellation

Natural events have had a significant impact on overall flight activity,and the aviation industry plays a vital role in helping society cope with the impact of these events.As one of the most impactful weather typhoon seasons appears and continues,airlines operating in threatened areas and passengers having travel plans during this time period will pay close attention to the development of tropical storms.This paper proposes a deep multimodal fusion and multitasking trajectory prediction model that can improve the reliability of typhoon trajectory prediction and reduce the quantity of flight scheduling cancellation.The deep multimodal fusion module is formed by deep fusion of the feature output by multiple submodal fusion modules,and the multitask generation module uses longitude and latitude as two related tasks for simultaneous prediction.With more dependable data accuracy,problems can be analysed rapidly and more efficiently,enabling better decision-making with a proactive versus reactive posture.When multiple modalities coexist,features can be extracted from them simultaneously to supplement each other’s information.An actual case study,the typhoon Lichma that swept China in 2019,has demonstrated that the algorithm can effectively reduce the number of unnecessary flight cancellations compared to existing flight scheduling and assist the new generation of flight scheduling systems under extreme weather.

Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems

This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.

Frequency-Domain Wideband Acoustic Noise Cancellation System

When building an adaptive noise cancellation system for wideband acoustic signals, one can meet some difficulties in practical implementation of such a system. The major problem is related to the necessity of using real-time signal generation and processing. In this paper the active noise control system which utilizes adaptation in frequency domain is considered. It is shown that the proposed algorithms simplify practical implementation of a noise cancellation system. The results of computer simulations and prototype experiments show the effectiveness of the proposed methods. .

Group-Based Successive Interference Cancellation for Multi-Antenna NOMA System with Error Propagation

Non-orthogonal multiple access(NOMA)is viewed as a key technique to improve the spectrum efficiency and solve the issue of massive connectivity.However,for power domain NOMA,the required overall transmit power should be increased rapidly with the increasing number of users in order to ensure that the signal-to-interference-plus-noise ratio reaches a predefined threshold.In addition,since the successive interference cancellation(SIC)is adopted,the error propagation would become more serious as the order of SIC increases.Aiming at minimizing the total transmit power and satisfying each user’s service requirement,this paper proposes a novel framework with group-based SIC for the deep integration between power domain NOMA and multi-antenna technology.Based on the proposed framework,a joint optimization of power control and equalizer design is investigated to minimize transmit power consumption for uplink multi-antenna NOMA system with error propagations.Based on the relationship between the equalizer and the transmit power coefficients,the original problem is transformed to a transmit power optimization problem,which is further addressed by a parallel iteration algorithm.It is shown by simulations that,in terms of the total power consumption,the proposed scheme outperforms the conventional OMA and the existing cluster-based NOMA schemes.

Standardization of apple cancellation test for neglect patients in Korea:An observational study

BACKGROUND Neglect can be divided into two types using apple cancellation test(apple test):Egocentric neglect(EN)and allocentric neglect(AN).However,in South Korea,apple test results and decision criteria are still largely dependent on tests by foreign countries.AIM To establish a new South Korea standard and improve the accuracy of neglect assessment,the apple experiment was standardized in this study.METHODS This study was conducted on 223 healthy subjects for a total of 7 mo from August 2021 to February 2022.Standardization was carried out using the original apple test developed by Bickerton in 2011.In scoring for the apple test,total omission error refers to the number of missed targets(full apple)in the entire test sheet(left,middle,and right area).The score for EN is the difference between the correct number of right area and the correct number of left area(excluding the middle area).For AN,the score is difference between the number of left opening apples and number of right opening apples(including the middle area).Linear regression analysis was used for standardization using the general characteristics of subjects and the results of the apple test.RESULTS The cut-off score,which is the standard value indicating the pathological condition by combining the results of all subjects,is as follows:Total omission error(5),error for EN(2),and error for AN(2).Also,differences in cut-off score according to age were found.CONCLUSION This study will be helpful in facilitating a more accurate differential diagnosis of neglect.

Advanced surface coil layout with intrinsic noise cancellation properties for surface-NMR applications

A recent study demonstrated that in small-scale prepolarized surface nuclear magnetic resonance(SNMR-PP)measurements with a footprint of a few square meters,customized PP switch-off ramps can serve as an efficient excitation mechanism,eliminating the requirement for a conventional oscillating excitation pulse.This approach enables the detection of short relaxation signals from the unsaturated soil zone and can,therefore,be used to directly provide soil moisture and pore geometry information.Because ultimately such small-scale SNMR-PP setups are intended for a mobile application,it is necessary to develop strategies that allow for speedy measurement progress and do not require noise cancellation protocols based on reference stations.Hence,we developed a new concentric figure-of-eight(cFOE)loop layout that combines the direction independence of a circular loop with the intrinsic noise cancellation properties of a classical FOE-loop.This approach significantly decreases the measurement time because suitable signal-to-noise ratios are reached much faster compared to a classical circular loop and will bring us one step further toward fast and non-invasive soil moisture mapping applications.

Practical Considerations for Implementing Adaptive Acoustic Noise Cancellation in Commercial Earbuds

Active noise cancellation has become a prominent feature in contemporary in-ear personal audio devices.However,due to constraints related to component arrangement,power consumption,and manufacturing costs,most commercial products utilize fixed-type controller systems as the basis for their active noise control algorithms.These systems offer robust performance and a straightforward structure,which is achievable with cost-effective digital signal processors.Nonetheless,a major drawback of fixed-type controllers is their inability to adapt to changes in acoustic transfer paths,such as variations in earpiece fitting conditions.Therefore,adaptive-type active noise control systems that employ adaptive digital filters are considered as the alternative.To address the increasing system complexity,design concepts and implementation strategies are discussed with respect to actual hardware limitations.To illustrate these considerations,a case study showcasing the implementation of a filtered-x least mean square-based active noise control algorithm is presented.A commercial evaluation board accommodating a low-cost,fixed-point digital signal processor is used to simplify operation and provide programming access.The earbuds are obtained from a commercial product designed for noise cancellation.This study underscores the importance of addressing hardware constraints when implementing adaptive active noise cancellation,providing valuable insights for real-world applications.

Active Cancelation of Acoustic Noise in Waveguides by Standard Control Task Decision Usage

Cybernetic decision variants were analyzed in order to use for physical task of active noise cancelation. 10 dB mean active noise cancellation is demonstrated in two decades frequency band by usage of cybernetic decision for acoustical duct physical scale model. The used decision was found on minimization of acoustical field power transfer function from the beginning of waveguide to their end.

Digital Cancellation Scheme and Hardware Implementation for High-Order Passive Intermodulation Interference Based on Hammerstein Model

Passive intermodulation(PIM)interference urgently needs to be solved in the satellite communication system,owing to degrading the whole performance.Mainstream research contributions to the cancellation method for PIM were focused on the analog domain,however,the PIM distortion cannot be eliminated completely with the approaches.Meanwhile,some researchers attempt to tackle the problem through digital signal processing,nevertheless,the proposed methods were not suitable for the practical satellite communication scenario.In this paper,we present a general scheme for the adaptive feedforward PIM cancellation.High-order PIM signals at baseband are estimated by modeling the PIM distortion with Hammerstein model in the digital domain.Based on the reconstructed PIM signal,we adopt the least mean square algorithm to adaptively mitigate the PIM interference for tracking the variation of PIM.The time and frequency synchronization of PIM are based on the correlation of the peak of received signals with the corresponding reconstructed PIM signal.Practical experimental results show that the scheme can effectively cancel the PIM interference,and achieve an interference suppression gain more than 20dB.

Using LMS Adaptive Filter in Direct Wave Cancellation

The way to use the least-mean-square (LMS) arithmetic to cancel the direct wave for a passive radar system is introduced. The model of the direct wave is deduced. By using the LMS adaptive FIR filter, the software solution for FM passive radar system is developed instead of the hardware consumption of the existent experiment system of passive radar. Further more some simulative results are given. The simulative results indicate that using LMS arithmetic to cancel the direct wave is effective.

Interference Cancellation in Device-to-Device Communications underlying MU-MIMO Cellular Networks

This paper investigates the device-to-device(D2 D) communication underlaying multi-user multi-input multi-output(MU-MIMO) cellular networks. It is assumed that D2 D users reuse the downlink time-frequency resources of cellular links, and the base station(BS) is assumed to be equipped with multiple antennas. We investigate the ergodic achievable sum rate of the system when the interference cancellation(IC) precoding strategy is employed at the BS. The distributions of the received signal-to-interference-plus-noise ratio(SINR) for each link are firstly analyzed, and an exact ergodic achievable sum rate of the whole system with closedform expressions is then derived. Furthermore, we present novel upper and lower bounds with simpler expressions, which are later verified to be fairly close to the Monte-Carlo simulations. All the expressions we presented are suitable for arbitrary network topology and arbitrary number of antennas at BS. Based on the derived bounds, the influence of the antennas at BS on system performance is then analyzed. We reveal that the system performance increases along with the number of antennas at BS in a logarithmic way. The accuracy of our analytical results is validated via comparisons with Monte-Carlo simulations.

Method of moving target detection based on sub-image cancellation for single-antenna airborne synthetic aperture radar

The method of moving target detection based on subimage cancellation for single-antenna airborne SAR is presented. First the subimage is obtained through frequency processing is pointed out. The imaging difference of a stationary objects and moving object in the subimage based on the frequency division is analyzed from the fundamental principle. Then the developed method combines the shear averaging algorithm to focus on the moving target in the subimage, after the clutter suppression and the focusing position in each subimage is obtained. Next the observation model and the relative movement of the moving targets between the subimages estimate the moving targets. The theoretical analysis and simulation results demonstrate that the method is effective and can not only detect the moving targets, but also estimate their motion parameters precisely.

ADAPTIVE HARMONIC CANCELLATION APPLIED IN ELECTRO-HYDRAULIC SERVO SYSTEM WITH ANN

The method for harmonic cancellation based on artificial neural network (ANN)is proposed. The task is accomplished by generating reference signal with frequency that should beeliminated from the output. The reference input is weighted by the ANN in such a way that it closelymatches the harmonic. The weighted reference signal is added to the fundamental signal such thatthe output harmonic is cancelled leaving the desired signal alone. The weights of ANN are adjustedby output harmonic, which is isolated by a bandpass filter. The above concept is used as a basis forthe development of adaptive harmonic cancellation (AHC) algorithm. Simulation results performedwith a hydraulic system demonstrate the efficiency and validity of the proposed AHC control scheme.

New Parallel Interference Cancellation Scheme for DS/CDMA Systems

This paper proposes a new multi-stage parallel interference cancellation scheme by modifying the conventional multi-stage parallel interference canceller (PIC). At each stage, it first converts the interference-cancelled outputs from previous stage into thea prior information, in terms of which the bit mean values are computed and the multi-access interference (MAI) for each user is evaluated, and then an interference cancellation is performed to obtain further interference suppression. To reduce the implementation complexity, we give an approximation expression for bit mean value. The performance over AWGN channel is analyzed and compared to the conventional PIC. The user numberK=7 and spreading factorN=13 are chosen as simulation parameters. The computer simulation results show that the proposed PIC has better performance than the conventional PIC both with 2 interference cancellation (IC) stages, at bit error rate of 10?3, for example, about 3 dB performance gain is obtained by using the proposed PIC. It is also shown that our proposed PIC with 1-stage is superior to the conventional PIC with 2-stage in performance, which is of practical value because PIC with fewer stages can bring about shorter processing delay. Key words CDMA - parallel interference cancellation - multi-access interference CLC number TN 914 Foundation item: Supported by the National Natural Science Foundation of China (69772015)Biography: Xu Guo-xiong (1967-), male, Ph. D candidate, research direction: wireless communication.

On the Performance of Active Analog Self-Interference Cancellation Techniques for Beyond 5G Systems

The in-band full-duplex(IBFD)mechanism is of interest in beyond 5 G systems due to its potential to enhance spectral efficiency and reduce delay.To achieve the maximum gain of IBFD systems,the significant self-interference(SI)must be efficiently suppressed.The challenges of wideband selfinterference cancellation(SIC)lie in the radio frequency(RF)domain,where the performance will be limited by the hardware.This paper reviews current RF cancellation mechanisms and investigates an efficient mechanism for future wideband systems with minimum complexity.The working principle and implementation details of multi-tap cancellers are first introduced,then an optical domain-based RF canceller is reviewed,and a novel low-cost design is proposed.To minimize the cost and complexity of the canceller,the minimum required number of taps are analyzed.Simulation results show that with the commonly used 12-bits analog-to-digital converter(ADC)at the receiver,the novel optical domain-based canceller can enable efficient SIC in the 3 GPP LTE specifications compatible system within 400 MHz bandwidth.

Cancellation Strategy in Rollback Mechanism

Rollback is a synchronization mechanism in optimistic parallel discrete event simulation （PDES）. A basic and popular realization of rollback is based on cancellation of error executed messages. In this paper, several cancellation strategies are introduced, and a new method proposed. Performance comparison is made based on experimental results.

Application of pole-zero cancellation circuit in nuclear signal filtering and shaping algorithm

In radiation measurement and digital nuclear spectrum systems,traditional nuclear signal processing circuits in nuclear electronics have been gradually replaced by digital algorithm modules with the application of highperformance programmable hardware logic devices(such as FPGA or DSP).Referring to the digital realization method of inverse RC integral circuit systems,the function of the pole-zero cancellation(PZC)circuit was analyzed,a new modified cascade equivalent model of PZC was established,and the time-domain digital PZC(DPZC)recursive algorithm was derived in detail in this study.Two parameters kIand k_(D)are included in the new algorithm,where kIshould match the exponential decay time constant of the input signal to realize the pole-zero compensation,while the decay time constant of the output signal can be changed with the adjustable parameter k_(D)(which is larger than the decay time constant of the input signal).Based on the new DPZC algorithm module,two trapezoidal(triangular)shaping filters were designed and implemented.The amplitude–frequency characteristics of the output signal of the proposed trapezoidal shaping algorithm and the convolution trapezoidal shaping algorithm were compared,with fixed peaking time.The results show that the trapezoidal shaping algorithm based on DPZC can better suppress high-frequency noise.Finally,based on the Na I(Tl)scintillator(u75 mm×75 mm)detector and^(137)Cs source,the effect of the k_(D)value on the energy resolution of the DPZC trapezoidal(triangular)shaping algorithm was studied.The experimental results show that,with an increase in k_(D),the energy resolution of the system improved and reached the maximum when k_(D)was greater than 10,and the optimal energy resolution of the system was 7.72%.

Noise cancellation of a multi-reference full-wave magnetic resonance sounding signal based on a modified sigmoid variable step size least mean square algorithm

Nano-volt magnetic resonance sounding(MRS) signals are sufficiently weak so that during the actual measurement, they are affected by environmental electromagnetic noise, leading to inaccuracy of the extracted characteristic parameters and hindering effective inverse interpretation. Considering the complexity and non-homogeneous spatial distribution of environmental noise and based on the theory of adaptive noise cancellation, a model system for noise cancellation using multi-reference coils was constructed to receive MRS signals. The feasibility of this system with theoretical calculation and experiments was analyzed and a modified sigmoid variable step size least mean square(SVSLMS) algorithm for noise cancellation was presented. The simulation results show that, the multi-reference coil method performs better than the single one on both signal-to-noise ratio(SNR) improvement and signal waveform optimization after filtering, under the condition of different noise correlations in the reference coils and primary detecting coils and different SNRs. In particular, when the noise correlation is poor and the SNR<0, the SNR can be improved by more than 8 dB after filtering with multi-reference coils. And the average fitting errors for initial amplitude and relaxation time are within 5%. Compared with the normalized least mean square(NLMS) algorithm and multichannel Wiener filter and processing field test data, the effectiveness of the proposed method is verified.

Multi-channel differencing adaptive noise cancellation with multi-kernel method

Although a various of existing techniques are able to improve the performance of detection of the weak interesting sig- nal, how to adaptively and efficiently attenuate the intricate noises especially in the case of no available reference noise signal is still the bottleneck to be overcome. According to the characteristics of sonar arrays, a multi-channel differencing method is presented to provide the prerequisite reference noise. However, the ingre- dient of obtained reference noise is too complicated to be used to effectively reduce the interference noise only using the clas- sical linear cancellation methods. Hence, a novel adaptive noise cancellation method based on the multi-kernel normalized least- mean-square algorithm consisting of weighted linear and Gaussian kernel functions is proposed, which allows to simultaneously con- sider the cancellation of linear and nonlinear components in the reference noise. The simulation results demonstrate that the out- put signal-to-noise ratio （SNR） of the novel multi-kernel adaptive filtering method outperforms the conventional linear normalized least-mean-square method and the mono-kernel normalized least- mean-square method using the realistic noise data measured in the lake experiment.