{"title":"Naive, robust or fully-adaptive: An estimation problem for CES distributions","authors":"M. Greco, S. Fortunati, F. Gini","doi":"10.1109/SAM.2014.6882441","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882441","url":null,"abstract":"In this paper we deal with the estimation of the covariance matrix for Complex Elliptically Symmetric (CES) data. We follow three different approaches with different level of knowledge on the specific CES model and we compare the asymptotic performances under the three approaches in terms of Cramér-Rao Bounds and Huber limit.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"301 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116790532","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}
{"title":"Sampling size in Monte Carlo Bayesian compressive sensing","authors":"I. Kyriakides, R. Pribic","doi":"10.1109/SAM.2014.6882426","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882426","url":null,"abstract":"Bayesian compressive sensing using Monte Carlo methods is able to handle non-linear, non-Gaussian signal models. The computational expense associated with Monte Carlo methods is, however, a concern especially in scenarios requiring real-time processing. In this work, a theoretical model is derived that provides insight on the relationship between performance and computational expense for a Monte Carlo Bayesian compressive sensing algorithm. The theoretical model is shown to accurately describe the practical performance of the algorithm. Additionally, the theoretical model is able to inexpensively project the algorithm's performance characteristics for various SNRs and computational complexity levels. The model is then useful in assessing the method's performance under different operational requirements.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122035040","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}
David Neumann, Andreas Gründinger, M. Joham, W. Utschick
{"title":"On the amount of training in coordinated massive MIMO systems","authors":"David Neumann, Andreas Gründinger, M. Joham, W. Utschick","doi":"10.1109/SAM.2014.6882399","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882399","url":null,"abstract":"Coordinated training significantly reduces the impact of pilot contamination in massive MIMO systems. Moreover, coordinated systems can use additional training resources in an effective manner, making it worthwhile to spend more resources on training than the necessary minimum. For a fixed channel coherence time, we analyze the trade-off between spending resources on training or data symbols for the uncoordinated and the coordinated case.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114839396","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}
Juan Augusto Maya, L. Vega, C. Galarza, A. Altieri
{"title":"Distributed detection of correlated random processes under energy and bandwidth constraints","authors":"Juan Augusto Maya, L. Vega, C. Galarza, A. Altieri","doi":"10.1109/SAM.2014.6882358","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882358","url":null,"abstract":"We analyze a binary hypothesis testing problem built on a wireless sensor network (WSN). Using Large Deviation Theory (LDT), we compute the probability error exponents of a distributed scheme for detecting a correlated circularly-symmetric complex Gaussian process under the Neyman-Pearson framework. Using an analog scheme, the sensors transmit scaled versions of their measurements several times through a multiple access channel (MAC) to reach the fusion center (FC), whose task is to decide whether the process is present or not. In the analysis, we consider the energy constraint on each node transmission. We show that the proposed distributed scheme requires relatively few MAC channel uses to achieve the centralized error exponents when detecting correlated Gaussian processes.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128168167","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}
José P. González-Coma, M. Joham, P. M. Castro, L. Castedo
{"title":"Power minimization in the multiple stream MIMO Broadcast Channel with imperfect CSI","authors":"José P. González-Coma, M. Joham, P. M. Castro, L. Castedo","doi":"10.1109/SAM.2014.6882366","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882366","url":null,"abstract":"We address the design of linear precoders and receivers in a MIMO Broadcast Channel (BC) with perfect Channel State Information (CSI) at reception but partial CSI at the transmitter. Our aim is to minimize the transmit power subject to per-user rate constraints when multiple streams of data are sent to each user. We develop a gradient-projection algorithm to convert the per-user constraints into per-stream constraints. The MIMO BC linear precoders and receivers that minimize the transmit power are then obtained with an alternating optimization algorithm.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129515562","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}
{"title":"Multidimensional ESPRIT: A coupled canonical polyadic decomposition approach","authors":"Mikael Sørensen, L. D. Lathauwer","doi":"10.1109/SAM.2014.6882437","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882437","url":null,"abstract":"The ESPRIT method is a classical method for one-dimensional harmonic retrieval. During the past two decades it has become apparent that several applications in signal processing correspond to the less studied Multi-dimensional Harmonic Retrieval (MHR) problem. In order to accommodate this demand, we propose an extension of ESPRIT to MHR based on the coupled canonical polyadic decomposition. This leads to a dedicated uniqueness condition and an algebraic framework for MHR.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"67 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133454493","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}
Lu Wang, L. Albera, A. Kachenoura, H. Shu, L. Senhadji
{"title":"CP decomposition of semi-nonnegative semi-symmetric tensors based on QR matrix factorization","authors":"Lu Wang, L. Albera, A. Kachenoura, H. Shu, L. Senhadji","doi":"10.1109/SAM.2014.6882439","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882439","url":null,"abstract":"The problem of Canonical Polyadic (CP) decomposition of semi-nonnegative semi-symmetric three-way arrays is often encountered in Independent Component Analysis (ICA), where the cumulant of a nonnegative mixing process is frequently involved, such as the Magnetic Resonance Spectroscopy (MRS). We propose a new method, called JDQR+, to solve such a problem. The nonnegativity constraint is imposed by means of a square change of variable. Then the high-dimensional optimization problem is decomposed into several sequential rational subproblems using QR matrix factorization. A numerical experiment on simulated arrays emphasizes its good performance. A BSS application on MRS data confirms the validity and improvement of the proposed method.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131174807","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}
{"title":"Correlated UE impairments in ZF MU-MIMO transmissions","authors":"M. Müller, Michael Meidlinger, M. Rupp","doi":"10.1109/SAM.2014.6882405","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882405","url":null,"abstract":"Applying Multiple Input Multiple Output (MIMO) techniques in wireless communication allows the parallel transmission of several data streams, thus increasing the throughput while leaving the transmit power unchanged. However, the maximum number of parallel streams is defined by the minimum of transmit- or receive-antennas, where in the downlink the User Equipment (UE) is most likely the limiting factor. To overcome this situation, multiple UEs can be served in parallel by Multi User (MU)-MIMO. Zero Forcing MU-MIMO is a low complex technique that tries to cancel the interference between the streams already at the Base Transceiver Station and that requires only one receive antenna per UE. However, due to various transmission impairments, there exists some residual interference degrading the performance. In this paper we illustrate the negative effects of correlated UEs by providing measurement and simulation results. The measurements are carried out with the Vienna MIMO Testbed and not only is the channel estimation performed by measurements, but also the data transmission is performed over physical channels.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125135095","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}
{"title":"Application of Krylov based methods in calibration for radio astronomy","authors":"A. M. Sardarabadi, A. V. D. Veen","doi":"10.1109/SAM.2014.6882363","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882363","url":null,"abstract":"As the number of antennas in the modern radio-telescopes increases, the computational complexity of the calibration algorithms becomes more and more important. In this paper we use the Khatri-Rao structure of the covariance data model used for such calibrations and combine it with Krylov subspace based methods to achieve accurate calibration results with low complexity, very small memory usage and fast convergence properties. We also demonstrate the proposed method on experimental data measured by the LOFAR radio-telescope.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114515196","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}
K. Alexandris, Alexios Balatsoukas-Stimming, A. Burg
{"title":"Measurement-based characterization of residual self-interference on a full-duplex MIMO testbed","authors":"K. Alexandris, Alexios Balatsoukas-Stimming, A. Burg","doi":"10.1109/SAM.2014.6882408","DOIUrl":"https://doi.org/10.1109/SAM.2014.6882408","url":null,"abstract":"Full-duplex communication systems require very strong self-interference suppression. Unfortunately, perfect suppression is not possible in practice and some residual self-interference remains. This residual self-interference acts as additive noise whose statistical properties may be different from those of thermal noise. This work presents a measurement-based study of the statistical properties of residual self-interference on an OFDM based full-duplex MIMO testbed. Moreover, we quantify the effect that residual self-interference has on some popular MIMO receivers and we employ a strategy to reduce the performance impact of residual-self interference.","PeriodicalId":141678,"journal":{"name":"2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115072891","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}