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Adaptation with reduced-size message pass to precoder selection in multi-cell MIMO systems

Adaptation with reduced-size message pass to precoder select...

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sensor array and multichannel signal processing workshop

作者： Igor M. Guerreiro Charles C. Cavalcante Dennis Hui Wireless Telecommunications Research Group Universidade Federal do Ceará Fortaleza Brazil Ericsson Research San José CA USA

ISBN: (纸本)9781509021048

This paper addresses the optimization of a multicell network where each cell needs to select precoding matrices for beamforming in a distributed way. A modified version of the adaptive min-sum algorithm that considers reduced-size messages in the message-passing procedure is proposed. The message-passing technique, where each message is reduced to convey only part of usual information, is applied to maximize the system throughput leading to a faster adaptation procedure. Simulation results show this reduction leads to a small average performance loss in system throughput of approximately 6%, while generally reduces the message size in about 73%. Also, the proposed method still outperforms the baseline greedy technique.

关键词： Throughput Niobium Indexes Measurement MIMO Precoding array signal processing

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Multi-task wireless acoustic sensor network for node-specific speech enhancement and DOA estimation

Multi-task wireless acoustic sensor network for node-specifi...

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sensor array and multichannel signal processing workshop

作者： Amin Hassani Jorge Plata-Chaves Alexander Bertrand Marc Moonen Department of Electrical Engineering-ESAT KU Leuven Leuven Belgium

ISBN: (纸本)9781509021048

We consider the design of a distributed algorithm that is suitable for a wireless acoustic sensor network formed by nodes solving multiple tasks (MDMT). In the network, some of the nodes aim at estimating the node-specific direction-of-arrival of some desired sources. Additionally, there are other nodes that aim at implementing either a multi-channel Wiener filter or a minimum variance distortionless response beamformer in order to estimate node-specific desired signals as they impinge on their microphones. By using compressive filter-and-sum operations that incorporate a low-rank approximation of the sensor signal correlation matrix, the proposed MDMT algorithm let the nodes cooperate to achieve the network-wide centralized solution of their node-specific estimation problems without any knowledge about the tasks of other nodes. Finally, the effectiveness of the algorithm is shown through computer simulations.

关键词： Estimation Microphones Speech signal processing algorithms Direction-of-arrival estimation Wireless sensor networks Wireless communication

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Single snapshot DOA estimation in the presence of mutual coupling for arbitrary array structures

Single snapshot DOA estimation in the presence of mutual cou...

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sensor array and multichannel signal processing workshop

作者： Ahmet M. Elbir T. Engin Tuncer Dept. of Electrical and Electronics Engineering Middle East Technical University Ankara TURKEY

ISBN: (纸本)9781509021048

In this paper, single snapshot direction-of-arrival (DOA) estimation under mutual coupling (MC) is considered with arbitrary array structures. A compressed sensing approach is utilized and a joint-sparse recovery algorithm is proposed. In this respect, both spatial source directions and MC coefficients are embedded into a joint-sparse vector. A new dictionary matrix is defined using the symmetricity of MC matrix. The proposed approach does not depend on the structure of MC matrix and it is suitable for any type of array geometry. In the simulations, the proposed method is evaluated for a planar array where the antennas are placed randomly in 2-D space. It is shown that the proposed method effectively estimates the source parameters and performs significantly better than the alternative methods.

关键词： Symmetric matrices Direction-of-arrival estimation Estimation Antenna arrays Transmission line matrix methods Dictionaries

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A robust beamformer with main beam control

A robust beamformer with main beam control

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sensor array and multichannel signal processing workshop

作者： Bin Liao Chongtao Guo Lei Huang Qiang Li H. C. So College of Information Engineering Shenzhen University Shenzhen China Department of Electronic Engineering City University of Hong Kong Kowloon Hong Kong SAR China

ISBN: (纸本)9781509021048

In this paper, a new robust beamforming approach which is capable of accurately controlling the main beam response is proposed. In this method, steering vector uncertainties are taken into account in the beamformer design problem with array magnitude response constraints. This allows us to control the main beam as prescribed. However, the resultant non-convex problem has a different formulation from that of the existing methods for robust beamforming with magnitude response constraints. Thus, existing techniques cannot be applied directly. To cope with this problem, the lower and upper norm bounds of the beamformer weight vector are first derived. The semidefinite relaxation technique is then employed as an approximate solver ending up with a grid search solution. Simulation results show that the proposed method is able to accurately control the main beam magnitude response in the presence of steering vector uncertainties.

关键词： Uncertainty Robustness array signal processing Covariance matrices Linear programming sensor arrays Electronic mail

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Two-dimensional DOA estimation using parallel coprime subarrays

Two-dimensional DOA estimation using parallel coprime subarr...

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sensor array and multichannel signal processing workshop

作者： Si Qin Yimin D. Zhang Moeness G. Amin Villanova University Villanova PA US Department of Electrical and Computer Engineering Temple University Philadelphia PA USA Center for Advanced Communications Villanova University Villanova PA USA

ISBN: (纸本)9781509021048

A conventional coprime array is a linear array, which consists of two uniform linear subarrays to construct an effective difference coarray with certain desirable characteristics. In this paper, we propose a parallel coprime array structure and a novel algorithm for two-dimensional (2-D) direction-of-arrival (DOA) estimation. By vectorizing the cross-covariance matrix of subarray data, the resulting virtual difference coarray enables resolving more signals than the number of antennas. The 2-D DOA estimation problem is cast as two separate one-dimensional DOA estimation problems, where the estimated azimuth and elevation angles can be properly associated. Compared with other methods, such as, the propagator method (PM) and the rank-reduction (RARE) based algorithms, the proposed method resolves more signals and achieves improved estimation performance.

关键词： Estimation Direction-of-arrival estimation sensor arrays signal resolution Covariance matrices

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Improving spectral efficiency in large-array FDD systems with hybrid beamforming

Improving spectral efficiency in large-array FDD systems wit...

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sensor array and multichannel signal processing workshop

作者： Daniel C. Araújo Eleftherios Karipidis André L. F. de Almeida João C. M. Mota Group of Wireless Communication Research (GTEL) Ceará Brazil Ericsson Research Stockholm Sweden

We investigate the spectral efficiency of large-array systems serving a single-antenna user in cellular frequencies, using full digital or hybrid analog-digital beamforming in frequency division duplexing (FDD) or time division duplexing (TDD) mode. We consider downlink transmission in time-frequency coherent channel blocks, containing both the pilots and data. Considering FDD and taking the pilot overhead into account, we show that hybrid beamforming provides better spectral efficiency performance than full digital beamforming, mainly in cases with high mobility and many antenna elements. We also optimize the number of used radio chains for hybrid beamforming in FDD and show it is possible to achieve comparable spectral efficiency as with full digital beamforming in TDD.

关键词： array signal processing Radio frequency OFDM Antennas MIMO Channel estimation Time-frequency analysis

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Shift invariance, incomplete arrays and coupled CPD: A case study

Shift invariance, incomplete arrays and coupled CPD: A case ...

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sensor array and multichannel signal processing workshop

作者： Mikael Sørensen Lieven De Lathauwer KU Leuven Kulak Engineering and Technology Kortrijk Belgium

Tensors have proven to be useful tools for array processing. Most attention has been paid to separable arrays, which lead to a Canonical Polyadic Decomposition (CPD). For more general geometries, and in particular for sparse arrays and arrays with missing sensors, more general tensor methods are required. The recently proposed coupled CPD framework allows a data fission/fusion approach in which one zooms in on partial structures and combines the partial CPDs through which the latter are imposed. This approach yields explicit algebraic conditions under which the solution is unique. The exact solution can be found with a matrix eigenvalue decomposition in the noiseless case, similar to ESPRIT in the case of uniform linear arrays. We study in detail the case of sparse spatial sampling where sensors are located on points of a two-dimensional grid. Despite the fact that the array is incomplete, coupled CPD allows us to exploit the rectangularity of the grid as well as the uniformity of the spatial sampling in both dimensions.

关键词： Tensile stress sensor arrays Matrix decomposition Antenna arrays Direction-of-arrival estimation

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Acoustic image estimation using fast transforms

Acoustic image estimation using fast transforms

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sensor array and multichannel signal processing workshop

作者： Vítor H. Nascimento Mateus C. Silva Bruno S. Masiero University of São Paulo São Paulo Brazil Campinas University of Campinas Brazil

ISBN: (纸本)9781509021048

The estimation of acoustic images is a computationally-intensive task for large microphone arrays. One of the most popular algorithms for acoustic image estimation, delay-and-sum beamforming (DAS), has low computational complexity, but low spatial resolution. Several methods have been developed to obtain higher resolution, among which compressive beamforming, which is based on sparse estimation. Although this method does achieve higher resolution, its computational complexity is significantly higher than that of DAS. In this paper we describe the use of the Kronecker array transform (KAT) to accelerate DAS and specific algorithms for sparse estimation, in particular matching pursuit (MP) and the spectral projected-gradient algorithm SPGL1. In addition, we describe how the nonequispaced fast Fourier transform (NFFT) can be used to provide further acceleration.

关键词： Transforms Microphone arrays Matching pursuit algorithms Acoustics array signal processing Acceleration

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Robust MISO downlink: An efficient algorithm for improved beamforming directions

Robust MISO downlink: An efficient algorithm for improved be...

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sensor array and multichannel signal processing workshop

作者： Mostafa Medra Timothy N. Davidson Department of Electrical and Computer Engineering McMaster University Hamilton Ontario Canada

ISBN: (纸本)9781509021048

The design of a set of beamformers for the multiple-input single-output (MISO) downlink that provides the scheduled users with the quality-of-service (QoS) level that they requested can be quite sensitive to the accuracy of the channel state information (CSI) that is available at the base station. To mitigate that sensitivity, models for the uncertainty in the CSI can be incorporated in the design formulation, but the resulting optimization problems are typically difficult to solve. A recently developed low-complexity algorithm for the power loading problem, in which the beamforming directions are pre-defined, has demonstrated good performance in numerical experiments. In this paper the reasons that underlie that good performance are examined. Then, using insights from that analysis, a computationally-efficient algorithm for jointly designing the beamforming directions and the power loading is developed. The resulting beamformers provide a significant reduction in the outage probability, and a hybrid of the two algorithms provides even further reduction.

关键词： Uncertainty array signal processing Loading Algorithm design and analysis Approximation algorithms Channel estimation signal to noise ratio

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Cooperative navigation and coverage identification with random gossip and sensor fusion

Cooperative navigation and coverage identification with rand...

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sensor array and multichannel signal processing workshop

作者： André R. Braga Marcelo G. S. Bruno Carsten Fritsche Fredrik Gustafsson Division of Electronics Engineering Aeronautics Institute of Technology Brazil Linkopings universitet Linkoping SE Department of Electrical Engineering Linköping University Linköping Sweden

ISBN: (纸本)9781509021048

This paper is concerned with cooperative Terrain Aided Navigation of a network of aircraft using fusion of Radar Altimeter and inter-node range measurements. State inference is performed using a Rao-Blackwellized Particle Filter with online measurement noise statistics estimation. For terrain coverage measurement noise parameter identification, an online Expectation Maximization algorithm is proposed, where local sufficient statistics at each node are calculated in the E-step, which are then distributed to neighboring nodes using a random gossip algorithm to perform the M-step at each node. Simulation results show that improvement on positioning and calibration performance can be achieved compared to a non-cooperative approach.

关键词： Aircraft Aircraft navigation Atmospheric modeling Estimation Hidden Markov models Noise measurement

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