the proceedings contain 113 papers. the topics discussed include: a comparative study of blind channel identification methods for alamounti coded systems over indoor transmissions at 2.4 GHZ;rapid prototyping of a cos...
ISBN:
(纸本)9781424422418
the proceedings contain 113 papers. the topics discussed include: a comparative study of blind channel identification methods for alamounti coded systems over indoor transmissions at 2.4 GHZ;rapid prototyping of a cost effective and flexible 4×4 MIMO testbed;a low complexity decoding scheme for quasi-orthogonal space-time block coding;experimental investigation of polarization diversity;deterministic MIMO channel order estimation based on canonical correlation analysis;spectrum sharing in wireless networks: a QoS-aware secondary multicast approach with worst user performance optimization;optimality of multichannel beamforming for spatially correlated multiple-antenna Rayleigh fading channels with channel covariance information at transmitter;and comparison of the CAF-DF and SAGE algorithms in multiple channel parameter estimation.
the following topics are dealt with: arrayprocessing for communications; DOA estimation and localization; radar; sensor networks and distributed estimation; beamforming; speech/audio/acoustic arrayprocessing; detect...
the following topics are dealt with: arrayprocessing for communications; DOA estimation and localization; radar; sensor networks and distributed estimation; beamforming; speech/audio/acoustic arrayprocessing; detection and estimation; blind source separation.
the problem of interest is the determination of the location of a licensed or unlicensed source of radio transmission from air. Accordingly, an experiment was conducted in 2008 involving a two-dimensional antenna arra...
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the interplay between signalprocessing and wireless networking plays a crucial role in sensor networks deployed for detection and estimation applications. In this paper, an opportunistic power assignment strategy for...
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ISBN:
(纸本)9781424422401
the interplay between signalprocessing and wireless networking plays a crucial role in sensor networks deployed for detection and estimation applications. In this paper, an opportunistic power assignment strategy for IR-UWB sensor networks is presented which is designed to optimize detection performance in terms of the global probability of error. the opportunistic power assignment strategy utilizes boththe detection error probabilities of individual sensors as well as network topology information, leading to significant performance gains compared to uniform power assignment.
this paper discusses the maximum number of sources when their direction of arrivals (DOAs) are estimated by the method of direction estimation (MODE), and presents a modified version of MODE that can estimate more num...
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ISBN:
(纸本)9781728119465
this paper discusses the maximum number of sources when their direction of arrivals (DOAs) are estimated by the method of direction estimation (MODE), and presents a modified version of MODE that can estimate more number of sources than that by the original MODE. It is well-known that M-element array can basically estimate up to (M - 1) DOAs, however the application of MODE may reduce up to M/2 DOAs because of its computation procedure. We propose a novel DOA estimation method by modifying MODE to employ peak-search of the primary eigenvector beam patterns instead of the null-search in the original MODE. Performance of the proposed method is evaluated through computer simulation.
Since the number of independent array data snapshots is limited by the availability of real-world data, we propose a parametric bootstrap for resampling. the proposed parametric bootstrap is based on a generative adve...
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ISBN:
(纸本)9781728119465
Since the number of independent array data snapshots is limited by the availability of real-world data, we propose a parametric bootstrap for resampling. the proposed parametric bootstrap is based on a generative adversarial network (GAN) following the generative approach to machine learning. For the GAN model we chose the Wasserstein GAN with penalized norm of gradient of the critic with respect to its input (wGAN_gp). the approach is demonstrated with synthetic and real-world ocean acoustic array data.
We propose a scalable and energy efficient method for reconstructing a 'sparse' Gauss-Markov random field that is observed by an array of sensors and described over wireless channels to a fusion center. the en...
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ISBN:
(纸本)9781424422401
We propose a scalable and energy efficient method for reconstructing a 'sparse' Gauss-Markov random field that is observed by an array of sensors and described over wireless channels to a fusion center. the encoder is universal, i.e. invariant to the statistical model of the source and the channel, and is based on compressed sensing. the reconstruction algorithms exploit the a-priori statistical information about the field and the channel at the fusion center to yield a performance comparable to information theoretic bounds. Furthermore, by putting stringent constraints on the sensing matrix we avoid (or even eliminate) inter-sensor communication while suffering negligible degradation in performance.
this paper is devoted to the problem of source detection with large sensor networks, in a context where the number of available samples N and the number of antennas M are of the same order of magnitude. We focus here ...
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ISBN:
(纸本)9781467310710
this paper is devoted to the problem of source detection with large sensor networks, in a context where the number of available samples N and the number of antennas M are of the same order of magnitude. We focus here on the popular likelihood penalization (LP) methods, such as Minimum Description Length (MDL) or Akaike Information Criterion (AIC). Such methods have been widely studied in the context where N >> M, and in particular the consistency of the MDL and the inconsistency of the AIC estimator were established in the asymptotic regime where N -> infinity while M remains constant. We propose here an analysis in the asymptotic regime where M, N both converge to infinity at the same rate, and using results from random matrix theory, we establish conditions on the penalty term to ensure consistency of LP methods in this latter regime. As a consequence, we deduce that the MDL method is always inconsistent while the AIC method can be consistent in certain situations.
In this paper, we propose angle of arrival estimation algorithms for arbitrary array geometries. the proposed methods extend the root-WSF [1] and Modified Variable Projection (MVP) [2] algorithms to arbitrary array co...
ISBN:
(纸本)9781424422401
In this paper, we propose angle of arrival estimation algorithms for arbitrary array geometries. the proposed methods extend the root-WSF [1] and Modified Variable Projection (MVP) [2] algorithms to arbitrary array configurations. this is accomplished by employing the recently introduced Manifold Separation Technique (MST) [3], which stems from wavefield modelling [4]. the algorithms process the data in the element-space domain, i.e. no mapping of the data that introduces errors is required. Moreover, coherent sources can be handled. the proposed MST-based MVP algorithm shows a statistical performance close to the Cramer-Rao Lower Bound (CRLB) [5, 6]. the performance is illustrated using calibration data from two real-world arrays.
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