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Computationally Efficient Maximum Likelihood Channel Estimation for Coarsely Quantized Massive MIMO Systems

IEEE COMMUNICATIONS LETTERS 2022年第2期26卷 444-448页

作者： Liu, Fangqing Shang, Xiaolei Cheng, Yuanbo Zhang, Guoyang Univ Sci & Technol China Dept Elect Engn & Informat Sci Hefei 230027 Anhui Peoples R China

We consider computationally efficient maximum likelihood (ML) channel estimation for massive multiple-input multiple-output (MIMO) systems using coarsely quantized measurements obtained from low-resolution analog-to-digital converters (ADCs) at the receivers. We first devise a computationally efficient ML estimator (referred to as CQML) by using the cyclic optimization and majorization-minimization (MM) techniques. Then, we show the connections between CQML and the conventional unquantized ML estimator. Numerical examples are provided to demonstrate the effectiveness and computational efficiency of the proposed channel estimation algorithm.

关键词： Maximum likelihood estimation Channel estimation Massive MIMO Quantization (signal) signal processing algorithms Convex functions Convergence Low-resolution analog-to-digital converters (ADCs) massive multiple-input multiple-output (MIMO) communications maximum likelihood (ML) channel estimation majorization-minimization (MM)

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A Resolution-Improved Imaging Algorithm Based on Uniform Circular Array

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IEEE ANTENNAS AND WIRELESS PROPAGATION LETTERS 2022年第3期21卷 461-465页

作者： Yuan, Hang Chen, Yi-Jun Luo, Ying Liang, Jia Wang, Zhi-Hao Air Force Engn Univ Inst Informat & Nav Xian 710077 Peoples R China Collaborat Innovat Ctr Informat Sensing & Underst Xian 710077 Peoples R China Xidian Univ Natl Key Lab Radar Signal Proc Xian 710071 Peoples R China Engn Univ PAP Coll Informat Engn Xian 710086 Peoples R China

Radar imaging can provide important information of target for recognition. However, due to the limited azimuth resolution, it is difficult to improve the imaging quality of the existing imaging technology based on the uniform circular array (UCA), due to the Bessel function modulation in the frequency domain of the echo received by the UCA. A resolution-improved imaging method based on the uniform circular array antenna (UCA) is proposed. The time-frequency dual relationship between vortex electromagnetic echo and UCA echo is deduced;on this basis, the Bessel function modulation compensation method is constructed to realize the azimuth high-resolution imaging of the target. The algorithm process is based on a UCA echo, which is independent of vortex electromagnetic waves. Theoretical analysis and simulation show that, compared with the existing vortex electromagnetic wave radar imaging methods, the azimuth resolution of the proposed method is improved.

关键词： Radar imaging Imaging Azimuth Radar Image resolution signal processing algorithms Antenna arrays Antenna array azimuth resolution radar imaging uniform circular array (UCA)

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A Secondary Path-Decoupled Active Noise Control Algorithm Based on Deep Learning

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IEEE signal processing LETTERS 2022年 29卷 234-238页

作者： Chen, Daocheng Cheng, Longbiao Yao, Dingding Li, Junfeng Yan, Yonghong Inst Acoust Key Lab Speech Acoust & Content Understanding Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100190 Peoples R China

Active noise control (ANC) systems are widely used to cancel unwanted noise. However, for high-level noise, the residual error signal cannot be fully eliminated because of the nonlinearity of the secondary path, resulting in the diverging of the adaptive filter. In this letter, we propose a secondary path-decoupled ANC (SPD-ANC) algorithm based on deep learning. Specifically, the secondary path decoupled module consisting of two time-domain convolutional recurrent networks, one for modeling the nonlinear secondary path and the other for modeling the reverse process, is employed to calculate the secondary path-decoupled (SPD) error signal. The control signal is then generated by an adaptive filter that is optimized towards minimizing the SPD error signal. Simulation results indicate that the proposed method outperforms the conventional ANC methods under different conditions.

关键词： Adaptation models signal processing algorithms Actuators Training Mathematical models Deep learning Time-domain analysis Active noise control deep learning nonlinear secondary path adaptive filter

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Learning-Based Sparse Recovery for Joint Activity Detection and Channel Estimation in Massive Random Access Systems

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IEEE WIRELESS COMMUNICATIONS LETTERS 2022年第11期11卷 2295-2299页

作者： Shiv, U. K. Sreeshma Bhashyam, Srikrishna Srivatsa, Chirag Ramesh Murthy, Chandra R. IIT Madras Dept Elect Engn Chennai 600036 Tamil Nadu India Indian Inst Sci Dept Elect & Commun Engn Bengaluru 560012 India

We consider the problem of joint activity detection and channel estimation in massive random access. When the receiver has multiple antennas, this is a joint sparse recovery problem with multiple measurement vectors (MMV). For the general setting where the channels could be correlated across antennas, we first develop a modified minimum mean squared error (MMSE) shrinkage function to be used in the Trainable Iterative Soft Thresholding Algorithm (TISTA). Then, we learn this MMSE shrinkage function using a model-based neural network. In the simulation results, the proposed learning-based method, L-MMSE-MMV-TISTA, offers a 30-40% reduction in preamble length requirement compared to TISTA. We also compare L-MMSE-MMV-TISTA with the state-of-the-art MMV sparse Bayesian learning (M-SBL) method. While M-SBL can provide better performance at the cost of higher complexity in highly measurement-constrained settings, LMMSE-MMV-TISTA provides a significant complexity advantage when only a slightly larger number of measurements are available.

关键词： Training Estimation Channel estimation Antenna measurements Sparse matrices signal processing algorithms Data models Massive random access sparse recovery activity detection sparse Bayesian learning iterative soft thresholding

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A Data-Driven Waveform Adaptation Method for Mm-Wave Gait Classification at the Edge

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IEEE signal processing LETTERS 2022年 29卷 26-30页

作者： Hor, Soheil Pilanci, Mert Arbabian, Amin Stanford Univ Elect Engn Dept Stanford CA 94305 USA

The ever-increasing need for real-time 3D perception for autonomy has resulted in development of a new generation of high-resolution perception sensors paired with powerful edge processors and advanced perception algorithms. However, processing of the large data volumes generated by such high-resolution sensors still imposes a great challenge for resource-limited edge devices and systems. In this work, we visit this problem in the context of pedestrian gait analysis using high-resolution mm-Wave sensors with application in autonomous driving. We propose reducing the total computational load of a resource-limited perception system by dynamically controlling the mm-Wave sensor's resolution on the fly. We provide results on three dynamic sensor adaptation approaches including an end-to-end Deep Q-Learning approach that can overcome the resource and performance limitations inherent to conventional static methods.

关键词： Three-dimensional displays Q-learning Program processors signal processing algorithms Dynamic scheduling Control systems Sensor systems Deep neural networks mm-wave sensing gait recognition reinforcement learning

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Parallel Pipelined Architecture and Algorithm for Matrix Transposition Using Registers

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第3期69卷 1627-1631页

作者： Zhang, Bo Ma, Zhenguo Luo, Wei Zhejiang Univ Coll Biomed Engn & Instrument Sci Hangzhou 310027 Peoples R China Chinese Univ Hong Kong Dept Biomed Engn Hong Kong Peoples R China

In this brief, we present a new algorithm and architecture for continuous-flow matrix transposition using registers. The algorithm supports P-parallel matrix transposition. The hardware architecture reaches the theoretical minimums in terms of latency and memory. It is composed of a group of identical cascaded basic swap circuits, whose stages are determined by the corresponding algorithm, and can be controlled via a set of counters. Compared with the state-of-the-art architecture, the proposed architecture supports matrices whose rows and columns are integer multiples of P. Here P can be arbitrary, including but not limited to power-of-two integers. Moreover, our results provide additional insight into continuous-flow non-square matrix transposition.

关键词： Computer architecture Arrays Hardware signal processing algorithms Registers Parallel processing Circuits and systems Pipelined algorithm hardware architecture continuous-flow matrix transposition parallel computing

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Affine Projection Champernowne Algorithm for Robust Adaptive Filtering

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2022年第3期69卷 1947-1951页

作者： Kumar, Krishna Karthik, M. L. N. S. Bhattacharjee, Sankha Subhra George, Nithin, V Indian Inst Technol Gandhinagar Dept Elect Engn Gandhinagar 382355 India

The recently proposed affine projection Versoria (APV) algorithm has been widely used over other affine based algorithms due to its robustness against impulsive noises. However, the performance of the APV algorithm suffers from high steady state misalignment. In order to overcome this, we propose affine projection Champernowne adaptive filter (APCMAF) in which instead of taking Versoria function as a cost function we have used the probability density function of the Champernowne distribution as a cost function and data reuse technique. The proposed APCMAF algorithm provides low steady-state misalignment in impulsive noise environment. To verify the performance of the APCMAF algorithm, a set of simulation study has been done in system identification scenarios which confirms that the APCMAF provides better steady state performance with improved convergence performance over other existing algorithms in impulsive noise environments. Further, the bound of learning rate for stable convergence has been also derived and a detailed comparison of computational complexity is also presented.

关键词： signal processing algorithms Convergence Adaptive filters Computational complexity Steady-state Cost function System identification Adaptive filter impulsive noises affine projection Champernowne function system identification

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An Explicit Connection Between Independent Vector Analysis and Tensor Decomposition in Blind Source Separation

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IEEE signal processing LETTERS 2022年 29卷 1277-1281页

作者： Ruan, Haoxin Lei, Tong Chen, Kai Lu, Jing Nanjing Univ Inst Acoust Key Lab Modern Acoust Nanjing 210093 Peoples R China Horizon Robot NJU Horizon Intelligent Audio Lab Beijing 100094 Peoples R China Nanjing Inst Adv Artificial Intelligence Nanjing 210014 Peoples R China

Independent vector analysis (IVA) and tensor decomposition are two types of effective algorithms for joint blind source separation (JBSS) with different statistical assumptions. Although IVA and tensor decomposition are intrinsically linked, their explicit connection has not been reported. In this letter, we reveal their explicit connection through a piecewise stationary multivariate complex Gaussian signal model. With this model, IVA can be explained as reconstructing the covariances of the mixtures in a similar manner as double coupled canonical polyadic decomposition (DC-CPD), a typical tensor-based algorithm, with the only difference being the distance metric used in the cost function. Numerical experiments show that IVA can achieve better separation performance but is highly dependent on how well the a priori model matches the actual signal, while DC-CPD is more robust to the model mismatch.

关键词： Tensors Covariance matrices Cost function Analytical models signal processing algorithms Numerical models Indexes Double coupled canonical polyadic decompos- ition independent vector analysis piecewise stationary Gaussian model tensor decomposition

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Dual-Frequency Quantum Phase Estimation Mitigates the Spectral Leakage of Quantum algorithms

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IEEE signal processing LETTERS 2022年 29卷 1222-1226页

作者： Xiong, Yifeng Ng, Soon Xin Long, Gui-Lu Hanzo, Lajos Univ Southampton Sch Elect & Comp Sci Southampton SO17 1BJ Hants England Tsinghua Univ Beijing 100084 Peoples R China

Quantum phase estimation is an important component in diverse quantum algorithms. However, it suffers from spectral leakage, when the reciprocal of the record length is not an integer multiple of the unknown phase, which incurs an accuracy degradation. For the existing single-sample estimation scheme, window-based methods have been proposed for spectral leakage mitigation. As a further advance, we propose a dual-frequency estimator, which asymptotically approaches the Cramer-Rao bound, when multiple samples are available. Numerical results show that the proposed estimator outperforms the existing window-based methods, when the number of samples is sufficiently high.

关键词： Phase estimation Maximum likelihood estimation signal processing algorithms Registers Probability distribution Frequency control Computers Algorithmic error mitigation dual-frequency estimator quantum algorithms quantum phase estimation

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Smart DC Optimizer for DC Series Arc Fault Detection and Extinguishing

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IEEE TRANSACTIONS ON POWER ELECTRONICS 2022年第9期37卷 10117-10121页

作者： Park, Hwa-Pyeong Kim, Mina Chae, Suyong Korea Inst Energy Res KIER Daejeon 34129 South Korea Korea Elect Technol Inst KETI Naju 13509 South Korea Pohang Univ Sci & Technol POSTECH Pohang 37673 South Korea

A dc arc faultdetection has been studied to improve the reliability of renewable energies and energy storage systems. In this Letter, the control algorithm of dc optimizer is proposed to detect the dc series arc fault condition between the PV panel and dc optimizer. The operational principle of the detection algorithm considers the characteristics of both the PV panel and arc fault, which can detect and extinguish the dc series arc fault condition. The validity of the proposed algorithm is verified through the simulation and experimental results.

关键词： Circuit faults Resistance Fault detection Voltage control signal processing algorithms Load modeling Integrated circuit modeling Arc discharges fault diagnosis DC-DC power converters photovoltaic systems

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