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2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)最新文献

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Performance improvement for wideband DOA estimation with white noise reduction based on uniform linear arrays 基于均匀线性阵列的宽带DOA估计降噪性能改进
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-09-19 DOI: 10.1109/SAM.2016.7569673
M. R. Anbiyaei, W. Liu, D. McLernon
{"title":"Performance improvement for wideband DOA estimation with white noise reduction based on uniform linear arrays","authors":"M. R. Anbiyaei, W. Liu, D. McLernon","doi":"10.1109/SAM.2016.7569673","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569673","url":null,"abstract":"A method is proposed for reducing the effect of white noise in wideband uniform linear arrays via a combination of a judiciously designed transformation followed by highpass filters. The reduced noise level leads to a higher signal to noise ratio for the system, which can have a significant effect on the performance of various direction of arrival (DOA) estimation methods. As a representative example, the compressive sensing-based wideband DOA estimation method is employed here to demonstrate the improved estimation performance, this is confirmed by simulation results.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127300348","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 9
Hardware design and optimal ADC resolution for uplink massive MIMO systems 上行大规模MIMO系统的硬件设计和最佳ADC分辨率
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-09-19 DOI: 10.1109/SAM.2016.7569654
Daniel Verenzuela, Emil Björnson, M. Matthaiou
{"title":"Hardware design and optimal ADC resolution for uplink massive MIMO systems","authors":"Daniel Verenzuela, Emil Björnson, M. Matthaiou","doi":"10.1109/SAM.2016.7569654","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569654","url":null,"abstract":"This work focuses on the hardware design for the efficient operation of Massive multiple-input multiple-output (MIMO) systems. A closed-form uplink achievable data rate expression is derived considering imperfect channel state information (CSI) and hardware impairments. We formulate an optimization problem to maximize the sum data rate subject to a constraint on the total power consumption. A general power consumption model accounting for the level of hardware impairments is utilized. The optimization variables are the number of base station (BS) antennas and the level of impairments per BS antenna. The resolution of the analog-to-digital converter (ADC) is a primary source of such impairments. The results show the trade-off between the number of BS antennas and the level of hardware impairments, which is important for practical hardware design. Moreover, the maximum power consumption can be tuned to achieve maximum energy efficiency (EE). Numerical results suggest that the optimal level of hardware impairments yields ADCs of 4 to 5 quantization bits.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133318041","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 31
Simplified performance comparison metric based on asymptotic threshold ranking for MIMO radar estimation 基于渐近阈值排序的MIMO雷达估计简化性能比较度量
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-09-19 DOI: 10.1109/SAM.2016.7569656
Qian He, Xiongwei Wu, Rick S. Blum
{"title":"Simplified performance comparison metric based on asymptotic threshold ranking for MIMO radar estimation","authors":"Qian He, Xiongwei Wu, Rick S. Blum","doi":"10.1109/SAM.2016.7569656","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569656","url":null,"abstract":"For many nonlinear estimation problems, classical lower bounds such as the Cramer-Rao bound (CRB) can characterize the mean squared error (MSE) performance only in the asymptotic region. While more powerful bounds like the Ziv-Zakai bound (ZZB) can also predict the best MSE performance in the nonasymptotic region, they may complicate the computation to an unaffordable extent. In this paper, for estimators with well-defined asymptotic threshold and virtually identical CRB, we propose to compare the MSE performance using the ZZB-based asymptotic threshold ranking. This method complements the CRB and is easier to compute than the ZZB, providing an efficient tool for preliminary system design.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122961559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Privacy preserving decentralized power system state estimation with phasor measurement units 基于相量测量单元的分散电力系统状态估计
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-09-15 DOI: 10.1109/SAM.2016.7569719
Neelabh Kashyap, S. Werner, Yih-Fang Huang, R. Arablouei
{"title":"Privacy preserving decentralized power system state estimation with phasor measurement units","authors":"Neelabh Kashyap, S. Werner, Yih-Fang Huang, R. Arablouei","doi":"10.1109/SAM.2016.7569719","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569719","url":null,"abstract":"This paper presents a privacy preserving approach to decentralized state estimation in multi-area power systems. By formulating state estimation as a model-distributed regularized least-squares (MDRLS) problem, we ensure that the state variables and system matrix of each area are hidden from all other areas in order to protect privacy and sensitive information. We present a scheme that solves the primal MDRLS problem using the alternating direction method of multipliers, and a second method that solves the dual problem using a distributed form of the coordinate descent algorithm. Only information related to current measurements on tie-lines linking neighboring areas is exchanged between those areas. The proposed schemes enable the local state estimator in each area to estimate the voltage magnitude and phase angle of each bus in its own control area from phasor measurement units (PMU) without the need for full local PMU-observability. The novelty of the proposed methods is in that they employ the inherently hierarchical architecture of the wide-area monitoring system to perform decentralized state estimation. Our simulation results show that the estimation error of both methods converges to that of the centralized approach.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133612307","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Point and beam-sparse radio astronomical source recovery using non-negative least squares 用非负最小二乘法恢复点和波束稀疏射电天文源
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-09-15 DOI: 10.1109/SAM.2016.7569681
S. Naghibzadeh, A. M. Sardarabadi, A. V. D. Veen
{"title":"Point and beam-sparse radio astronomical source recovery using non-negative least squares","authors":"S. Naghibzadeh, A. M. Sardarabadi, A. V. D. Veen","doi":"10.1109/SAM.2016.7569681","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569681","url":null,"abstract":"A simple and novel algorithm for source recovery based on array data measurements in radio astronomy is proposed. Considering that a radioastronomical image is composed of both point sources and extended emissions, prior information on the images, namely non-negativity and substantial black background are taken into account to choose source representation basis functions. Dirac delta functions are chosen to represent point sources and a Gaussian function approximated from the main beam of the antenna array is selected to capture the extended emissions. We apply the non-negative least squares (NNLS) algorithm to estimate the basis coefficients. It is shown that the sparsity promoted by the NNLS algorithm based on the chosen basis functions results in a super-resolution (finer resolution than prescribed by the main beam of the antenna array pattern) estimate for the point sources and smooth recovery for the extended emissions.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130233368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Decentralized cooperative detection based on averaging consensus 基于平均共识的分散合作检测
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-13 DOI: 10.1109/SAM.2016.7569716
Wassim Suleiman, M. Pesavento, A. Zoubir
{"title":"Decentralized cooperative detection based on averaging consensus","authors":"Wassim Suleiman, M. Pesavento, A. Zoubir","doi":"10.1109/SAM.2016.7569716","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569716","url":null,"abstract":"In this paper, decentralized spectrum sensing in a network of multiple cooperative cognitive nodes is considered. Based on the averaging consensus protocol, we propose a decentralized implementation of the energy detector, which is conventionally applied for spectrum sensing in a centralized fashion. The exact (non-asymptotic) null distribution of the decentralized energy detector test statistic is derived and used to compute the test threshold. The communication overhead of our proposed detector is low compared to the existing decentralized spectrum sensing algorithms. Moreover, we extend the energy detector to the problem of detecting the number of sources impinging onto a network of sensors. Simulation results demonstrate that using a moderate number of averaging consensus iterations, the extended energy detector is able to detect the correct number of sources with high probability.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126029215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
Stream selection methods for non-regenerative MIMO relay networks 非再生MIMO中继网络的流选择方法
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569609
Cong Sun, Eduard Axel Jorswieck
{"title":"Stream selection methods for non-regenerative MIMO relay networks","authors":"Cong Sun, Eduard Axel Jorswieck","doi":"10.1109/SAM.2016.7569609","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569609","url":null,"abstract":"For general MIMO relay AF networks, transmitting different number of data streams lead to significantly different performances. Therefore stream selection is an important preprocessing to maximize the sum rate. We first show that the problem to select only one stream for networks with single antenna users is NP-hard. Then based on the Total Signal to Total Interference plus Noise Ratio model, the stream selection problem for the general MIMO relay AF network is simplified as a 0-1 quadratic programming. Two stream selection algorithms are proposed. One is to delete streams from the full set and the other is to add streams to the basic set. Simulations show that the two algorithms are efficient to achieve high sum rate in medium to high SNR and in low SNR scenarios, respectively; the model with the stream selection as preprocess well balances between the achieved sum rate and the computational cost.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125547247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A robust beamformer with main beam control 具有主波束控制的鲁棒波束形成器
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569642
B. Liao, Chongtao Guo, Lei Huang, Qiang Li, H. So
{"title":"A robust beamformer with main beam control","authors":"B. Liao, Chongtao Guo, Lei Huang, Qiang Li, H. So","doi":"10.1109/SAM.2016.7569642","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569642","url":null,"abstract":"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.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114900746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 5
Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor 基于Vandermonde因子的知情半非负矩阵分解的非线性移动传感器标定
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569735
Clément Dorffer, M. Puigt, G. Delmaire, G. Roussel
{"title":"Nonlinear mobile sensor calibration using informed semi-nonnegative matrix factorization with a Vandermonde factor","authors":"Clément Dorffer, M. Puigt, G. Delmaire, G. Roussel","doi":"10.1109/SAM.2016.7569735","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569735","url":null,"abstract":"In this paper we aim to blindly calibrate a mobile sensor network whose sensor outputs and the sensed phenomenon are linked by a polynomial relationship. The proposed approach is based on a novel informed semi-nonnegative matrix factorization with a Vandermonde factor matrix. The proposed approach outperforms a matrix-completion-based method in a crowdsensing-like simulation of particulate matter sensing.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116820695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 14
Analytical performance evaluation of multi-dimensional Tensor-ESPRIT-based algorithms for strictly non-circular sources 严格非圆源的多维张量- esprit算法分析性能评价
2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM) Pub Date : 2016-07-10 DOI: 10.1109/SAM.2016.7569659
Jens Steinwandt, F. Roemer, M. Haardt
{"title":"Analytical performance evaluation of multi-dimensional Tensor-ESPRIT-based algorithms for strictly non-circular sources","authors":"Jens Steinwandt, F. Roemer, M. Haardt","doi":"10.1109/SAM.2016.7569659","DOIUrl":"https://doi.org/10.1109/SAM.2016.7569659","url":null,"abstract":"Exploiting inherent signal structure is a common approach towards improving the performance of conventional parameter estimation algorithms. It has recently been shown that the multi-dimensional (RD) nature of the signals and their statistical properties, i.e., their second-order (SO) strictly non-circular (NC) structure, can be exploited simultaneously by R-D NC Tensor-ESPRIT-type algorithms. In this contribution, we develop an analytical first-order performance evaluation of R-D NC Standard Tensor-ESPRIT and R-D NC Unitary Tensor-ESPRIT. The derived expressions are asymptotic in the effective signal-to-noise ratio (SNR), i.e., they become exact for high SNRs or a large sample size. Moreover, apart from a zero mean and finite SO moments, no assumptions on the noise statistics are required. We show that as in the corresponding NC matrix case, the performance of R-D NC Standard Tensor-ESPRIT and R-D NC Unitary Tensor-ESPRIT is asymptotically identical. Simulations verify the derived expressions.","PeriodicalId":159236,"journal":{"name":"2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129863273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
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