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Wideband Beamforming With Rainbow Beam Training Using Reconfigurable True-Time-Delay Arrays for Millimeter-Wave Wireless [Feature]

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IEEE CIRCUITS AND SYSTEMS MAGAZINE 2022年第4期22卷 6-25页

作者： Lin, Chung-Ching Boljanovic, Veljko Yan, Han Ghaderi, Erfan Mokri, Mohammad Ali Gaddis, Jayce Jeron Wadaskar, Aditya Puglisi, Chase Mohapatra, Soumen Xu, Qiuyan Poolakkal, Sreeni Heo, Deukhyoun Gupta, Subhanshu Cabric, Danijela Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA Washington State Univ Pullman WA USA Univ Calif Los Angeles Dept Elect & Comp Engn Los Angeles CA 90095 USA

The decadal research in integrated true-time-delay arrays have seen organic growth enabling realization of wideband beamformers for large arrays with wide aperture widths. This article introduces highly reconfigurable delay elements implementable at analog or digital baseband that enables multiple Spatial signal processing (SSP) functions including wideband beamforming, wideband interference cancellation, and fast beam training. Details of the beam-training algorithm, system design considerations, system architecture and circuits with large delay range-to-resolution ratios are presented leveraging integrated delay compensation techniques. The article lays out the framework for true-time-delay based arrays in next-generation network infrastructure supporting 3D beam training in planar arrays, low latency massive multiple access, and emerging wireless communications standards.

关键词： Wireless communication Millimeter wave communication Three-dimensional displays Array signal processing signal processing algorithms Delays Arrays Reconfigurable networks

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Asymptotic Performance Prediction for ADMM-Based Compressed Sensing

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IEEE TRANSACTIONS ON signal processing 2022年 70卷 5194-5207页

作者： Hayakawa, Ryo Osaka Univ Grad Sch Engn Sci Osaka 5608531 Japan

In this paper, we propose a method to predict the asymptotic performance of the alternating direction method of multipliers (ADMM) for compressed sensing, where we reconstruct an unknown structured signal from its underdetermined linear measurements. The derivation of the proposed method is based on the recently developed convex Gaussian min-max theorem (CGMT), which can be applied to various convex optimization problems to obtain its asymptotic error performance. Our main idea is to analyze the convex subproblem in the update of ADMM iteratively and characterize the asymptotic distribution of the tentative estimate obtained at each iteration. However, since the original CGMT cannot be used directly for the analysis of the iterative updates, we intuitively assume an extended version of CGMT in the derivation of the proposed method. Under the assumption, the result shows that the update equations in ADMM can be decoupled into a scalar-valued stochastic process in the asymptotic regime with the large system limit. From the asymptotic result, we can predict the evolution of the error (e.g., mean-square-error (MSE) and symbol error rate (SER)) in ADMM for large-scale compressed sensing problems. Simulation results show that the empirical performance of ADMM and its prediction are close to each other in sparse vector reconstruction and binary vector reconstruction.

关键词： Optimization Compressed sensing signal processing algorithms Convex functions Prediction algorithms Matching pursuit algorithms Sensors Compressed sensing alternating direction method of multipliers convex Gaussian min-max theorem asymptotic performance

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A Novel Hypercube-Based Heuristic for Quantum Boolean Circuit Synthesis

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS 2022年第3期12卷 648-661页

作者： Jiang, Yu-Chi Tseng, Kuo-Chun Hua, Cheng-Yen Kuo, Shu-Yu Chou, Yao-Hsin Kuo, Sy-Yen Natl Taiwan Univ Dept Elect Engn Taipei 10617 Taiwan Natl Ilan Univ Dept Comp Sci & Informat Engn Yilan 26041 Taiwan Natl Chi Nan Univ Dept Comp Sci & Informat Engn Puli 54561 Taiwan Natl Chung Hsing Univ Dept Comp Sci & Engn Taichung 40227 Taiwan

Quantum computation has extraordinary capabilities for solving complicated problems. As quantum computations are reversible by nature, reversible circuits are important for the development of quantum computation techniques. Designing an effective and efficient method for synthesizing reversible circuits to reduce costs and stabilize circuit efficiency is crucial. The traditional synthesis methods of solving reversible circuits focus on the conversion efficiency rather than discussing the properties of the reversible function. Thus, this paper aims to propose a novel synthesis method that directly and efficiently optimizes reversible circuit synthesis with the properties of the reversible circuit. The proposed method converts the reversible function into a hypercube, allowing visual observations of the overall circuit. Two new indicators, the adjacent Hamming distance (AHD) and total cycle distance (TCD), aid in effective decision-making, generating shorter circuits. Furthermore, we use the generalized Toffoli gate set, which without requiring any additional ancilla bits and has applications in error correction and fault tolerance. The experimental results show that our method can find better solutions than traditional methods, significantly reducing the gate count, while the hypercube assists in synthesizing the reversible circuit.

关键词： Logic gates Hypercubes Quantum computing Circuit synthesis Wires signal processing algorithms Quantum circuit Quantum computing quantum Boolean circuits reversible circuits synthesis algorithm hypercube generalized Toffoli gate

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GNSS User Technology: State-of-the-Art and Future Trends

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IEEE ACCESS 2022年 10卷 39939-39968页

作者： Egea-Roca, Daniel Arizabaleta-Diez, Markel Pany, Thomas Antreich, Felix Lopez-Salcedo, Jose A. Paonni, Matteo Seco-Granados, Gonzalo Univ Autonoma Barcelona UAB Dept Telecommun & Syst Engn IEEC CERES Barcelona 08193 Spain Univ Bundeswehr Munchen Inst Space Technol & Space Applicat ISTA D-85577 Neubiberg Germany Aeronaut Inst Technol ITA BR-12228900 Sao Jose Dos Campos Brazil European Commiss Joint Res Ctr JRC I-21027 Ispra Italy

Advances in the miniaturization, computational capabilities, and cost reduction of semiconductor technology have made global navigation satellite systems (GNSSs) the favorite choice for positioning. Currently, positioning is a key factor for many essential tasks in our modern society and will become even more important with the advent of new concepts such as the Internet of Things (IoT), smart cities and autonomous driving. The extensive use of GNSSs in a wide range of applications has caused their migration from the professional segment to the mass-market segment in terms of both technology and performance. This presents new and more stringent requirements in terms of accuracy, robustness, ubiquity, and continuity for the original "open sky" GNSS design. GNSS technology has experienced an unprecedented evolution in the last decade, and it is expected to exponentially evolve in the next decade. This evolution is considered in this paper with the aim of providing a unified reference for current GNSS receiver technologies and solutions and its expected evolution in the next decade. We consider receiver concepts, antennae, RF front ends, digital signal processing, and positioning algorithms. The impacts on the different GNSS market segments and applications are also analyzed.

关键词： Global navigation satellite system Receivers signal processing algorithms Robustness Computer architecture Satellites Market research Positioning GNSS user segment evolution core technology algorithms receiver architecture

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Particle Swarm Optimization: A Comprehensive Survey

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IEEE ACCESS 2022年 10卷 10031-10061页

作者： Shami, Tareq M. El-Saleh, Ayman A. Alswaitti, Mohammed Al-Tashi, Qasem Summakieh, Mhd Amen Mirjalili, Seyedali Univ York Dept Elect Engn York YO10 5DD N Yorkshire England ASharqiyah Univ Coll Engn Dept Elect & Commun Engn Ibra 400 Oman Xiamen Univ Malaysia Sch Elect & Comp Engn Dept Informat & Commun Technol Sepang 43900 Malaysia Univ Texas MD Anderson Canc Ctr Dept Imaging Phys Houston TX 77030 USA Univ Albaydha Fac Adm & Comp Sci Albaydha Yemen Multimedia Univ Fac Engn Cyberjaya 63100 Selangor Malaysia Torrens Univ Australia Ctr Artificial Intelligence Res & Optimizat Fortitude Valley Qld 4006 Australia Yonsei Univ Yonsei Frontier Lab Seoul 03722 South Korea

Particle swarm optimization (PSO) is one of the most well-regarded swarm-based algorithms in the literature. Although the original PSO has shown good optimization performance, it still severely suffers from premature convergence. As a result, many researchers have been modifying it resulting in a large number of PSO variants with either slightly or significantly better performance. Mainly, the standard PSO has been modified by four main strategies: modification of the PSO controlling parameters, hybridizing PSO with other well-known meta-heuristic algorithms such as genetic algorithm (GA) and differential evolution (DE), cooperation and multi-swarm techniques. This paper attempts to provide a comprehensive review of PSO, including the basic concepts of PSO, binary PSO, neighborhood topologies in PSO, recent and historical PSO variants, remarkable engineering applications of PSO, and its drawbacks. Moreover, this paper reviews recent studies that utilize PSO to solve feature selection problems. Finally, eight potential research directions that can help researchers further enhance the performance of PSO are provided.

关键词： signal processing algorithms Optimization Particle swarm optimization Feature extraction Topology Birds Statistics Applications of PSO binary PSO evolutionary computation feature selection hybrid algorithms meta-heuristic algorithms particle swarm optimization PSO variants

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Centralized and Decentralized Channel Estimation in FDD Multi-User Massive MIMO Systems

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IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY 2022年第7期71卷 7325-7342页

作者： Rajoriya, Anupama Budhiraja, Rohit Hanzo, Lajos IIT Kanpur Dept Elect Engn Kanpur 208016 Uttar Pradesh India Univ Southampton Southampton SO17 1BJ Hants England

We design a centralized and a decentralized variational Bayesian learning (C- and D-VBL) algorithms for the base station (BS) of a frequency division duplex massive multiple input multiple output (mMIMO) cellular system, wherein users send compressed information for it to estimate their downlink channels. The BS in the decentralized algorithm consists of multiple processing units (PUs), and each PU separately estimates the channels of a group of users, by employing the proposed D-VBL algorithm. To reduce channel estimation error, the PUs exploit the structured sparsity inherent in multi-user mMIMO channels by exchanging information among themselves. We investigate the proposed C-VBL and low-complexity D-VBL algorithms and show that i) they substantially outperform the state-of-the-art centralized and decentralized algorithms in terms of the normalized mean squared error and the bit error rate. This is because they beneficially exploit the channel sparsity, while the existing state-of-the-art solutions fail to do so. The proposed D-VBL is also robust to PU failures, and provides a similar performance as its centralized counterpart (C-VBL), but with a much reduced complexity.

关键词： Channel estimation Clustering algorithms Computer architecture signal processing algorithms Bayes methods Antennas Downlink Decentralized architecture frequency division duplex variational Bayesian learning

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An Accelerated Expectation-Maximization Algorithm for Multi-Reference Alignment

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IEEE TRANSACTIONS ON signal processing 2022年 70卷 3237-3248页

作者： Janco, Noam Bendory, Tamir Tel Aviv Univ Sch Elect Engn IL-69978 Tel Aviv Israel

The multi-reference alignment (MRA) problem entails estimating an image from multiple noisy and rotated copies of itself. If the noise level is low, one can reconstruct the image by estimating the missing rotations, aligning the images, and averaging out the noise. While accurate rotation estimation is impossible if the noise level is high, the rotations can still be approximated, and thus can provide indispensable information. In particular, learning the approximation error can be harnessed for efficient image estimation. In this paper, we propose a new computational framework, called Synch-EM, that consists of angular synchronization followed by expectation-maximization (EM). The synchronization step results in a concentrated distribution of rotations;this distribution is learned and then incorporated into the EM as a Bayesian prior. The learned distribution also dramatically reduces the search space, and thus the computational load of the EM iterations. We show by extensive numerical experiments that the proposed framework can significantly accelerate EM for MRA in high noise levels, occasionally by a few orders of magnitude, without degrading the reconstruction quality.

关键词： signal to noise ratio Synchronization Noise measurement Image reconstruction signal processing algorithms Noise level Computational complexity Multi-reference alignment angular synchronization expectation-maximization

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Improved YOLOv4 Based on Attention Mechanism for Ship Detection in SAR Images

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IEEE ACCESS 2022年 10卷 23785-23797页

作者： Gao, Yunlong Wu, Zhiyong Ren, Ming Wu, Chuan Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Changchun 130033 Peoples R China Chinese Acad Sci Key Lab Airborne Opt Imaging & Measurement Changchun 130033 Peoples R China

Ship detection in synthetic aperture radar (SAR) images is an important and challenging work in the field of image processing. Traditional detection algorithms usually rely on handmade features or predefined thresholds, the different performance is obtained with varying degrees of prior knowledge, and it is difficult to take advantage of big data. Recently, deep learning algorithms have found wide applications in ship detection from SAR images. However, due to the complex backgrounds and multiscale ships, it is hard for deep networks to extract representative target features, which limits the ship detection performance to a certain extent. In order to tackle the above problems, we propose an improved YOLOv4 (ImYOLOv4) based on attention mechanism. Firstly, to achieve the best trade-off between detection accuracy and speed, we adopt the off-the-shelf YOLOv4 as our basic framework because of its fast detection speed. Secondly, a thresholding attention module (TAM) is introduced to suppress the adverse effect of complex backgrounds and noises. Besides, we embed channel attention module (CAM) into improved BiFPN as the feature pyramid network (FPN) to better enhance the discrimination of the multiscale target features. Finally, the decoupled head with two parallel branches improves the performance of classification and regression. The proposed method is evaluated on public SAR dataset and the experimental results demonstrate that it has higher efficiency and feasibility than other mainstream methods, yielding the accuracy of 94.16% at intersection over union of 0.5 and 58.19% at intersection over union of 0.75.

关键词： Marine vehicles Feature extraction Object detection Licenses Detectors signal processing algorithms Remote sensing Ship detection SAR attention decouple head YOLOv4

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One-Step Calculation Circuit of FFT and Its Application

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2022年第7期69卷 2781-2793页

作者： Liu, Yiyang Wang, Chunhua Sun, Jingru Du, Sichun Hong, Qinghui Hunan Univ Coll Comp Sci & Elect Engn Changsha 410082 Peoples R China

Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT) are core components in the field of signal processing. However, in the existing research, there is no fully analog circuit that can realize the one-step calculation of FFT. Therefore, in this paper, an analog circuit that can calculate FFT and its inverse transform IFFT in one-step is proposed. First, a circuit that can realize complex number operations is designed. On the basis of this structure, a fully analog circuit that can realize fast and efficient computing of FFT and IFFT in one-step is proposed. In addition, different coefficient matching can be obtained to achieve arbitrary points of FFT and IFFT by adjusting the resistance value of the memristor, which has good programmability. Specific examples are given in the paper to evaluate the proposed method. The PSPICE simulation results show that the average accuracy is above 99.98%. More importantly, the calculation speed has been greatly improved compared with MATLAB simulation. Finally, the proposed circuit can be used to quickly solve convolution operation, and the average accuracy can reach 99.95%.

关键词： signal processing algorithms Discrete Fourier transforms Memristors Computer architecture Analog circuits Integrated circuit modeling Hardware FFT IFFT circuit design memristor complex number operation

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Channel Estimation in MIMO Systems With One-Bit Spatial Sigma-Delta ADCs

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IEEE TRANSACTIONS ON signal processing 2022年 70卷 4681-4696页

作者： Sankar, R. S. Prasobh Chepuri, Sundeep Prabhakar Indian Inst Sci Dept Elect Commun Engn Bangalore 560012 Karnataka India

This paper focuses on channel estimation in single-user and multi-user MIMO systems with multi-antenna base stations equipped with 1-bit spatial sigma-delta analog-to-digital converters (ADCs). A careful selection of the quantization voltage level and phase shift used in the feedback loop of 1-bit sigma-delta ADCs is critical to improve its effective resolution. We first develop a quantization noise model for 1-bit spatial sigma-delta ADCs. Using the developed noise model, we then present a two-step channel estimation algorithm to estimate a multipath channel parameterized by the gains, angles of arrival (AoAs), and angles of departure (AoDs). Specifically, in the first step, the AoAs are estimated using uplink pilots, which excite all the angles uniformly. Next, in the second step, the AoDs are estimated by progressively refining uplink beams through a recursive bisection procedure followed by a weighted least squares path gain estimator. For this algorithm, we propose a technique to select the quantization voltage level and phase shift. Through numerical simulations, we demonstrate that with the proposed parametric channel estimation algorithm, MIMO systems with 1-bit spatial sigma-delta ADCs perform significantly better than those with regular 1-bit ADCs and are on par with MIMO systems having high-resolution ADCs.

关键词： Channel estimation Quantization (signal) MIMO communication Voltage Antenna arrays signal processing algorithms Millimeter wave communication Angular channel model channel estimation mmWave MIMO 1-bit quantization quantization noise modeling spatial sigma-delta ADC

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