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检索条件"任意字段=Sensor Array and Multichannel Signal Processing Workshop"

共 2593 条记录，以下是301-310 订阅

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Hybrid Beamforming Design for Downlink MU-MIMO-OFDM Millimeter-Wave Systems

Hybrid Beamforming Design for Downlink MU-MIMO-OFDM Millimet...

引用

sensor array and multichannel signal processing workshop

作者： Sepideh Gherekhloo Khaled Ardah Martin Haardt Communications Research Laboratory (CRL) TU Ilmenau Ilmenau Germany

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Hybrid beamforming (HBF) structures have been recently proposed as one of the solutions to reduce cost and energy consumption of fully-digital multi-user MIMO systems in the millimeter-wave range. However, most of the initial references on HBF design assume frequency-flat single-carrier MIMO systems. Their extension to the frequency-selective multi-carrier MIMOOFDM case is, in general, not a straightforward task, especially in partially-connected architectures. In this paper, we propose a new HBF design approach for multi-user massive MIMO-OFDM systems. Simulation results reveal that the proposed solution achieves a comparable performance to the benchmark methods in the fully-connected case, while significantly outperforming them in case of partially-connected architectures.

关键词： Energy consumption array signal processing Simulation Millimeter wave technology Interference Benchmark testing Downlink

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Greedy coordinate descent method on non-negative quadratic programming

Greedy coordinate descent method on non-negative quadratic p...

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sensor array and multichannel signal processing workshop

作者： Chenyu Wu Yangyang Xu Department of Mathematical Sciences Rensselaer Polytechnic Institute Troy NY USA

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

The coordinate descent (CD) method has recently become popular for solving very large-scale problems, partly due to its simple update, low memory requirement, and fast convergence. In this paper, we explore the greedy CD on solving non-negative quadratic programming (NQP). The greedy CD generally has much more expensive per-update complexity than its cyclic and randomized counterparts. However, on the NQP, these three CDs have almost the same per-update cost, while the greedy CD can have significantly faster overall convergence speed. We also apply the proposed greedy CD as a subroutine to solve linearly constrained NQP and the non-negative matrix factorization. Promising numerical results on both problems are observed on instances with synthetic data and also image data.

关键词： array signal processing Algorithms Conferences Memory management Complexity theory Quadratic programming Convergence

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Optimization Inspired Learning Network for Multiuser Robust Beamforming

Optimization Inspired Learning Network for Multiuser Robust ...

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sensor array and multichannel signal processing workshop

作者： Minghe Zhu Tsung-Hui Chang School of Science & Engineering The Chinese University of Hong Kong Shenzhen China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

For real-time wireless networks with strict latency and energy constraints, deep neural networks have been used to approximate the resource allocation solutions that are previously obtained by advanced but computationally expensive optimization algorithms. In this paper, we consider the multi-user beamforming design problem for sum rate maximization in multi-antenna interference channels. Specifically, we propose a gradient projection inspired recurrent neural network for efficient beamforming optimization. The key ingredient is to explore the structure of the gradient vector of the sum rate so that the network learns only a set of dimension reduced coefficients. Furthermore, we extend it to the robust beamforming design for worst-case sum rate maximization in the presence of bounded channel errors. Numerical results show that the proposed learning networks can achieve high accuracy of the sum rates while with significantly reduced runtime.

关键词： Runtime Recurrent neural networks array signal processing Wireless networks signal processing algorithms Real-time systems Interference channels

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Hybrid Interference Mitigation Using Analog Prewhitening

Hybrid Interference Mitigation Using Analog Prewhitening

引用

sensor array and multichannel signal processing workshop

作者： Wei Zhang Yi Jiang Bin Zhou Die Hu Dept. of Communication Science & Engineering Fudan University Shanghai China Key Laboratory of Wireless Sensor Network and Communications Chinese Academy of Sciences (CAS)

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Strong interferences occur in several wireless scenarios, such as full-duplex wireless communications and heterogenous networks in unlicensed spectrum. Because strong interferences can cause excessive quantization noise in the receiver’s analog-to-digital converters (ADC), mitigation of strong interferences needs to be conducted not only after but before the ADCs, i.e., via hybrid processing – an actively researched topic in recent years. In this paper, we propose to use an M-input M-output analog phase shifter network (PSN) between the receiving antennas and the ADCs to prewhiten spatially the interferences (plus signal and noise). This scheme, referred to as the Hybrid Interference Mitigation using Analog Prewhitening (HIMAP), requires no information about the interferences except an estimated spatial covariance matrix. Before the ADCs, the HIMAP scheme suppresses the strong interferences through optimizing the PSN; after the ADCs, the HIMAP suppresses the residual interferences through employing minimum mean squared error (MMSE) beamforming. The simulation results verify the effectiveness of the HIMAP scheme.

关键词： Wireless communication Wireless sensor networks Quantization (signal) array signal processing Simulation Phase shifters Interference

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Blind source separation methods based on output nonlinear correlation for bilinear mixtures of an arbitrary number of possibly correlated signals

Blind source separation methods based on output nonlinear co...

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sensor array and multichannel signal processing workshop

作者： Yannick Deville Shahram Hosseini IRAP (Institut de Recherche en Astrophysique et Planétologie) Université de Toulouse UPS CNRS CNES OMP Toulouse France

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Traditional Blind Source Separation (BSS) methods require quite restrictive properties from the source signals (typically, statistically independent or at least uncorrelated sources) and mixing transform (typically, linear instantaneous mixtures). In this paper, we address a much more complex case, where the considered deterministic source signals may be correlated (we only request the source vectors and some associated vectors to be linearly independent) and where the mixing transform is nonlinear (more precisely, bilinear, which is e.g. of high interest for Earth observation applications). We propose a separation principle leading to a new set of BSS algorithms applicable to an arbitrary number of sources and based on nonlinear correlation parameters. Moreover, we analyze the separability properties of this approach and thus show that it is guaranteed to separate the sources up to the trivial scale and permutation indeterminacies.

关键词： Earth Correlation array signal processing Conferences signal processing algorithms Transforms Blind source separation

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Distributed Nonnegative Tensor Canonical Polyadic Decomposition With Automatic Rank Determination

Distributed Nonnegative Tensor Canonical Polyadic Decomposit...

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sensor array and multichannel signal processing workshop

作者： Lei Cheng Xueke Tong Yik-Chung Wu Shenzhen Research Institute of Big Data The University of Hong Kong

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Nonnegative tensor canonical polyadic decomposition (CPD) has found wide-spread applications in various signal processing tasks. However, the implementation of most existing algorithms needs the knowledge of tensor rank, which is difficult to acquire. To address this issue, by interpreting the nonnegative CPD problem using probability density functions (pdfs), the problem is recasted as probabilistic inference with integrated feature of automatic rank determination. Furthermore, to scale the inference algorithm to massive data, its implementation under modern distributed computing architecture is investigated, giving rise to a distributed probabilistic nonnegative tensor CPD algorithm. Numerical studies are presented to show the remarkable performance of the proposed algorithms in terms of accuracy and scalability.

关键词： Tensors Scalability signal processing algorithms Distributed databases Computer architecture Probability density function Probabilistic logic

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Fast signal Retrieval of Sonar in the Presence of Impulse Noise

Fast Signal Retrieval of Sonar in the Presence of Impulse No...

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sensor array and multichannel signal processing workshop

作者： Qiang Li Lei Huang Liang Zhang Min Huang Bo Zhao Peichang Zhang Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ) College of Electronic and Information Engineering Shenzhen University Shenzhen China School of Information and Control Engineering China University of Mining and Technology Xuzhou China

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This work develops two fast echo signal retrieval algorithms for sonar, which are able to efficiently work in the presence of impulse noise. First, using spatial sparsity of sonar echo signal, an ${\ell _{2,1}}$-norm optimization model with lasso form is formulated in impulse noise environment. Then, in order to recover original signal quickly, a direct gradient ${\ell _{2,1}}$-norm algorithm is employed to solve the optimization problem, where the solution has closed form but two variables need to be initialized. Further, the original problem is transformed into a constrained minimization problem and then Lagrange multiplier method is used to find the solution. Experimental results show that the proposed two methods have similar mean square error (MSE) performance compared with traditional method using CVX optimization tool, however, computational complexities are greatly reduced.

关键词： array signal processing Conferences Sonar signal processing algorithms Mean square error methods Tools Minimization

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Extended Object Tracking Using Hierarchical Truncation Model with Partial-View Measurements

Extended Object Tracking Using Hierarchical Truncation Model...

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sensor array and multichannel signal processing workshop

作者： Yuxuan Xia Pu Wang Karl Berntorp Hassan Mansour Petros Boufounos Philip V. Orlik Chalmers University of Technology Sweden

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

This paper introduces the hierarchical truncated Gaussian model in representing automotive radar measurements for extended object tracking. The model aims at a flexible spatial distribution with adaptive truncation bounds to account for partial-view measurements caused by self-occlusion. Built on a random matrix approach, we propose a new state update step together with an adaptively update of the truncation bounds. This is achieved by introducing spatial-domain pseudo measurements and by aggregating partial-view measurements over consecutive time-domain scans. The effectiveness of the proposed algorithm is verified on a synthetic dataset and an independent dataset generated using the MathWorks Automated Driving toolbox.

关键词： Adaptation models Graphical models Radar measurements signal processing algorithms Radar Radar tracking Object tracking

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On the convergence of Jacobi-type algorithms for Independent Component Analysis

On the convergence of Jacobi-type algorithms for Independent...

引用

sensor array and multichannel signal processing workshop

作者： Jianze Li Konstantin Usevich Pierre Comon Shenzhen Research Institute of Big Data Shenzhen China CNRS CRAN Universite de Lorrainé Nancy France CNRS GIPSA-Lab Univ. Grenoble Alpes Grenoble France

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

Jacobi-type algorithms for simultaneous approximate diagonalization of real (or complex) symmetric tensors have been widely used in independent component analysis (ICA) because of their good performance. One natural way of choosing the index pairs in Jacobitype algorithms is the classical cyclic ordering, while the other way is based on the Riemannian gradient in each iteration. In this paper, we mainly review in an accessible manner our recent results in a series of papers about weak and global convergence of these Jacobitype algorithms. These results are mainly based on the Lojasiewicz gradient inequality.

关键词： Jacobian matrices Tensors Conferences signal processing algorithms Independent component analysis Approximation algorithms Cost function

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Iterative Tensor Receiver for MIMO-GFDM systems

Iterative Tensor Receiver for MIMO-GFDM systems

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sensor array and multichannel signal processing workshop

作者： Damir Rakhimov Sai Pavan Deram Bruno Sokal Kristina Naskovska André de Almeida Martin Haardt Communications Research Laboratory Ilmenau University of Technology Ilmenau Germany Department of Teleinformatics Engineering Federal University of Ceara (UFC) Fortaleza Brazil

ISBN: (数字)9781728119465

ISBN: (纸本)9781728119472

In this paper, we present a tensor MIMO-GFDM system model that is based on the double contraction operator. Based on the derived system model, we propose an iterative tensor based MIMOGFDM receiver, that is initialized with the channel estimation obtained via pilots transmitted in the first data frame. The proposed algorithm exploits the tensor structure by using several unfoldings of the received signal sequentially to obtain estimates of the transmitted symbols and the channel. Simulation results show the tensor gain for the proposed algorithm in addition to the improved channel estimation. Numerical results confirm that the receiver requires the same amount of pilots as the Zero Forcing (ZF) receiver, while having a better symbol error rate (SER) performance and a better channel estimation accuracy.

关键词： Tensors Error analysis Simulation Channel estimation signal processing algorithms Receivers Data models

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