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Performance Analysis of sparse array based Massive MIMO via Joint Convex Optimization

China Communications 2022年第3期19卷 88-100页

作者： Mengting Lou Jing Jin Hanning Wang Dan Wu Liang Xia Qixing Wang Yifei Yuan Jiangzhou Wang Future Research Lab China Mobile Research InstituteBeijing 100053China School of Engineering and Digital Arts University of KentCanterburyU.K.

Massive multiple-input multiple-output(MIMO)technology enables higher data rate transmission in the future mobile ***,exploiting a large number of antenna elements at base station(BS)makes effective implementation of massive MIMO challenging,due to the size and weight limits of the masssive MIMO that are located on each ***,in order to miniaturize the massive MIMO,it is crucial to reduce the number of antenna elements via effective methods such as sparse array *** this paper,a multiple-pattern synthesis is considered towards convex optimization(CO).The joint convex optimization(JCO)based synthesis is proposed to construct a codebook for ***,a criterion containing multiple constraints is developed,in which the sparse array is required to fullfill all ***,extensive evaluations are performed under realistic simulation *** results show that with the same number of antenna elements,sparse array using the proposed JCO-based synthesis outperforms not only the uniform array,but also the sparse array with the existing CO-based synthesis ***,with a half of the number of antenna elements that on the uniform array,the performance of the JCO-based sparse array approaches to that of the uniform array.

关键词： B5G 6G sparse array joint convex optimization massive MIMO system-level simulation

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Health monitoring of a complex structure using a sparse array of modally selective transducers

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NONDESTRUCTIVE TESTING AND EVALUATION 2005年第3期20卷 159-173页

作者： Harper, M. F. Thompson, M. Mecon Ltd Cambridge CB3 0AE England

We describe a novel method of monitoring the structural health of a lattice-like structure using a permanent sparse array of structural-acoustic modally selective transducers. The transducers are used to measure transfer functions across the structure. Changes in these transfer functions can indicate changes in the structure, including corrosion, cracking and physical damage. Combining information across the set of transfer functions can allow the location of a change in the structure to be pinpointed. The method makes possible low-cost, automatic monitoring of large complex lattice-like structures. In this paper, we report results of trials on a scale model of an offshore jacket (for example, the cross-braced structure that supports an oilfield production platform in the North Sea). Results demonstrate quite accurate location of damage at two well-separated points on the structure, using two different arrangements of acoustic sources and sensors. The first arrangement-in which sources are at the top and sensors at the bottom of the structure-showed limited vertical resolution of damage location. The second arrangement-with both sources and sensors at the top-shows much better vertical resolution. Best results would be obtained by deploying sensors at both top and bottom, but this is probably impractical on jackets. The main limitation was signal drift due to both electronic drift and temperature drift in the structure, which masks small changes in transfer functions caused by structural damage.

关键词： structural monitoring structural acoustics structural dynamics sparse array guided waves

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Underdetermined direction of arrival estimation of wideband signal based on sparse array

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IET MICROWAVES ANTENNAS & PROPAGATION 2022年第10期16卷 646-653页

作者： Wu, Fan Cao, Fei Zhang, Xurong Jiang, Nan Zhang, Yanhong Lu, Shikun High Tech Inst Xian Xian 710025 Peoples R China High Tech Inst Beijing Beijing Peoples R China

To solve the problem of the mismatch of the wideband underdetermined direction of arrival (DOA) estimation under the condition of the On-grid model, this paper extends the narrowband Off-Grid model to wideband and proposes a new DOA estimation algorithm for Off-Grid sources based on group sparsity. The proposed algorithm first obtains the preliminary estimation result under the current predefined discrete grid through the group sparsity wideband DOA estimation algorithm. Then, the Off-Grid optimisation problem is adopted to calculate the Off-Grid deviation vector. It is also assumed that the off-grid deviation vectors of each frequency subband are exactly the same, thereby reducing the number of parameters to be estimated. Therefore, the proposed algorithm can not only maintain similar or even better estimation accuracy but also greatly reduce the computational complexity. Finally, simulation is conducted and the results verify the effectiveness and performance of the proposed method.

关键词： vectors optimisation DOA estimation algorithm off-grid optimisation problem wideband signal wideband underdetermined direction on-grid model computational complexity direction-of-arrival estimation off-grid deviation vectors compressed sensing group sparsity underdetermined direction of arrival estimation sparse array

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Optimal Design of sparse array for Ultrasonic Total Focusing Method by Binary Particle Swarm Optimization

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IEEE ACCESS 2020年 8卷 111945-111953页

作者： Zhang, Han Bai, Bichao Zheng, Jianfeng Zhou, Yun Chinese Acad Sci Inst Acoust Key Lab Noise & Vibrat Beijing 100190 Peoples R China Changzhou Univ Sch Mech Engn Changzhou 213164 Peoples R China

Ultrasonic phased array technology is used in various fields. Traditional full phased arrays place elements in every position of a uniform lattice with half-wavelength spacing between the lattice points, so the hardware cost is very high. This paper introduces an automatically method to sparsify the full array method with well-controlled sidelobes and the main lobe. By calculating one-dimensional phased array patterns that can reflect phased array performance, the binary particle swarm optimization (BPSO) algorithm is used to optimize the array layout. The method initialized form full array and decreased several elements step by step, then, a sparse array with comprehensive acoustic performance close to the reference full array is obtained. By applying the proposed method to the sparse array design of total focusing method (TFM), the simulation results indicate that the proposed sparse total focusing method can greatly increase computational efficiency while providing significantly higher image quality. The BPSO can provide effective optimization design for sparse arrays.

关键词： Phased arrays Acoustics arrays Acoustic beams Ultrasonic transducer arrays Focusing Binary particle swarm optimization sparse array total focusing method ultrasonic phased array

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A 2D adaptive beamforming method in sparse array

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2017年 77卷 100-104页

作者： Zeng, Wenhao Li, Hongtao Zhu, Xiaohua Chen, Cheng Nanjing Univ Sci & Technol Nanjing 210094 Jiangsu Peoples R China

This study presents an Accelerated Proximal Gradient singular value thresholding based Linearly Constrained Singular Canceler (APG-LCSC) algorithm to improve the performance of two-dimensional (2D) adaptive beamforming in sparse array. Firstly, a signal model is established based on Matrix Completion (MC), which can be proved to meet Null Space Property (NSP). Subsequently, left and right singular value vector of the received signal matrix is achieved via MC, and then a linearly constrained-singular canceler is obtained by employing the singular value vector. The proposed algorithm decreases the required number of antennas, lowers the computational complexity and has a robust performance. Computer simulations demonstrate that the proposed APG-LCSC algorithm can acquire high accuracy of 2D beamforming in sparse array. (C) 2017 Elsevier GmbH. All rights reserved.

关键词： sparse array Adaptive beamforming Matrix completion Antenna arrays Signal processing

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A Sum-Difference Expansion Scheme for sparse array Construction Based on the Fourth-Order Difference Co-array

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IEEE SIGNAL PROCESSING LETTERS 2022年 29卷 2647-2651页

作者： Yang, Zixiang Shen, Qing Liu, Wei Cui, Wei Beijing Inst Technol Sch Informat & Elect Beijing 100081 Peoples R China Univ Sheffield Dept Elect & Elect Engn Sheffield S1 3JD England

A generalized sum-difference expansion scheme is proposed to construct sparse arrays based on the fourth-order difference co-array with increased degrees of freedom (DOFs). Different from existing structures, both the second-order sum and difference co-arrays are exploited in array construction under this scheme, leading to a large consecutive fourth-order difference co-array with its number of uniform DOFs (uDOFs) derived. To optimize the provided uDOFs, required design properties of the initial prototype arrays are discussed. Three examples are then provided to demonstrate its superior performance over existing structures in both resolution capacity and estimation accuracy.

关键词： Prototypes Sensor arrays Estimation White noise sparse matrices Signal resolution Signal processing algorithms Difference co-array DOA estimation fourth-order sparse array sum co-array

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An Improved PHD Filtering for DOA Tracking With sparse array via Unscented Transform Strategy

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS 2023年第8期70卷 3174-3178页

作者： Dong, Xudong Sun, Meng Zhao, Jun Zhang, Xiaofei Nanjing Univ Aeronaut & Astronaut Coll Elect & Informat Engn Nanjing 210000 Peoples R China Nanjing Univ Aeronaut & Astronaut Key Lab Dynam Cognit Syst Electromagnet Spectrum S Nanjing 210000 Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 201800 Peoples R China

Traditional direction of arrival (DOA) tracking methods are sensitive to the number of sources, and their performance degrades when the number of sources changes with time. To solve the problem of multi-sources time-varying DOA tracking, an improved probability hypothesis density (PHD) method for DOA tracking is proposed in this brief. We improve the particle diversity of the resampling method and enhance the tracking performance by preprocessing the predicted particles in the prediction step of the traditional PHD particle filtering method. Moreover, the proposed method is extended to sparse array scenario to further improve the DOA tracking accuracy. Performance of the algorithm can be demonstrated by simulations with better performance than the spatial smoothing PAST (SS-PAST) and existing PHD methods.

关键词： Probability hypothesis density (PHD) DOA tracking sparse array particle diversity unscented transform

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Novel DOAs estimation method based on Doppler aided Chinese remainder theorem with all phase DFT for multiple targets in sparse array

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IET RADAR SONAR AND NAVIGATION 2020年第10期14卷 1512-1520页

作者： Cao, Chenghu Zhao, Yongbo Pang, Xiaojiao Chen, Sheng Hu, Yili Xidian Univ Natl Lab Radar Signal Proc Xian 710071 Peoples R China Xidian Univ Informat Sensing & Understanding Xian 710071 Peoples R China

In this study, the authors take further insight into the sparse geometry which offers a larger array aperture than uniform linear array with the same number of physical sensors. A novel direction of arrivals (DOAs) estimation model with flexible sparse geometry, which possesses the potential to significantly improve the estimation performance especially when the placed space and the weight of carrier such as airborne radar are restricted, is proposed to offer a larger aperture compared with co-prime array. The proposed algorithm can estimate DOAs by solving phase ambiguity. To improve the capability of spectrum analysis in frequency domain, all phase discrete Fourier transform (DFT), which can effectively alleviate spectrum leakage compared with traditional DFT, is proposed to apply into DOAs estimation. Additionally, the performance on degrees of freedom can be considerably improved compared with the state of the art where all the targets can be distinguished by Doppler information of received echo signal. More importantly, the proposed algorithm can effectively deal with DOA-closely-spaced targets because the proposed algorithm does not require to estimate signal subspace with ill-conditioned steering matrices. Both the theoretical analysis and simulation results demonstrate that the proposed algorithm significantly improves DOAs estimation precision with less computation cost.

关键词： discrete Fourier transforms airborne radar array signal processing direction-of-arrival estimation matrix algebra novel DOAs estimation method Chinese remainder theorem phase DFT multiple targets sparse array larger array aperture uniform linear array physical sensors arrivals estimation model flexible sparse geometry multiply targets estimation performance placed space airborne radar larger aperture co-prime array phase ambiguity frequency domain Doppler frequency information received echo signal spectrum analysis phase discrete Fourier spectrum leakage traditional DFT Doppler information DOA-closely-spaced targets DOAs estimation precision

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High Frame Rate Volumetric Imaging of Microbubbles Using a sparse array and Spatial Coherence Beamforming

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IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL 2021年第10期68卷 3069-3081页

作者： Wei, Luxi Wahyulaksana, Geraldi Meijlink, Bram Ramalli, Alessandro Noothout, Emile Verweij, Martin D. Boni, Enrico Kooiman, Klazina van der Steen, Antonius F. W. Tortoli, Piero de Jong, Nico Vos, Hendrik J. Erasmus MC Dept Cardiol Univ Med Ctr Rotterdam NL-3015 CN Rotterdam Netherlands Univ Florence Dept Informat Engn I-50139 Florence Italy Delft Univ Technol ImPhys NL-2628 CJ Delft Netherlands

Volumetric ultrasound imaging of blood flow with microbubbles enables a more complete visualization of the microvasculature. sparse arrays are ideal candidates to perform volumetric imaging at reduced manufacturing complexity and cable count. However, due to the small number of transducer elements, sparse arrays often come with high clutter levels, especially when wide beams are transmitted to increase the frame rate. In this study, we demonstrate with a prototype sparse array probe and a diverging wave transmission strategy, that a uniform transmission field can be achieved. With the implementation of a spatial coherence beamformer, the background clutter signal can be effectively suppressed, leading to a signal to background ratio improvement of 25 dB. With this approach, we demonstrate the volumetric visualization of single microbubbles in a tissue-mimicking phantom as well as vasculature mapping in a live chicken embryo chorioallantoic membrane.

关键词： Imaging array signal processing Spatial coherence Clutter Ultrasonic imaging Spirals Signal to noise ratio Coherence beamforming high frame rate microbubbles sparse array volumetric imaging

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Evolutionary Strategy-Based Location Algorithm for High-Resolution Lamb Wave Defect Detection With sparse array

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IEEE TRANSACTIONS ON ULTRASONICS FERROELECTRICS AND FREQUENCY CONTROL 2021年第6期68卷 2277-2293页

作者： Chen, Honglei Liu, Zenghua Gong, Yu Wu, Bin He, Cunfu Beijing Univ Technol Fac Mat & Mfg Beijing 100124 Peoples R China Beijing Univ Technol Beijing Engn Res Ctr Precis Measurement Technol & Beijing 100124 Peoples R China

Intelligent defect location algorithms based on the times-of-flight (ToFs) of Lamb waves are attractive for nondestructive testing (NDT) and structural health monitoring (SHM) of structures with large geometric sizes. Unlike the classical imaging algorithm based on projecting the amplitude information of scattering signals into a discrete spatial grid on the structure via their propagation characteristics, intelligent defect location algorithms are more efficient in specific applications. In our previous work, an intelligent algorithm for the location of defects in plates was proposed by considering the statistical, diversity, and fuzzy characteristics of the classical defect location algorithm. This approach can realize the efficient location of different defects under a suitable parameter selection. However, interfering components remain in the results, which decreases the detection resolution. Because the measurement uncertainty is directly related to the time, an optimized intelligent location algorithm is provided for the efficient defect location with Lamb waves and a sparse transducer array in this study. The defect position is identified with high resolution by analyzing the distribution of individuals. Several specific data and a fuzzy control parameter are introduced to the proposed algorithm. The K-means algorithm was adopted to realize the adaptive updating of individuals. The influence of parameter values on the detection results was analyzed. A combined analysis of the individuals was provided to ensure the detection robustness by eliminating the influence of fuzzy control parameters on the detection. Compared with the elliptic imaging algorithm, the intelligent defect location algorithm has higher location resolution and executes approximately 65 times faster.

关键词： Imaging Trajectory Transducers Scattering Fuzzy control Clustering algorithms Approximation algorithms Evolutionary strategy (ES) intelligent detection K-means algorithm Lamb waves sparse array

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