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Search Results: 1 - 10 of 11 matches for " Fyhn "
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Spectral Compressive Sensing with Polar Interpolation
Karsten Fyhn,Hamid Dadkhahi,Marco F. Duarte
Mathematics , 2013,
Abstract: Existing approaches to compressive sensing of frequency-sparse signals focuses on signal recovery rather than spectral estimation. Furthermore, the recovery performance is limited by the coherence of the required sparsity dictionaries and by the discretization of the frequency parameter space. In this paper, we introduce a greedy recovery algorithm that leverages a band-exclusion function and a polar interpolation function to address these two issues in spectral compressive sensing. Our algorithm is geared towards line spectral estimation from compressive measurements and outperforms most existing approaches in fidelity and tolerance to noise.
Review of Survey activities 2006: Cenozoic evolution of the Vietnamese coastal margin
Fyhn, Michael B.,Nielsen, Lars Henrik,Boldreel, Lars Ole
Geological Survey of Denmark and Greenland Bulletin , 2007,
Abstract:
Demodulating Subsampled Direct Sequence Spread Spectrum Signals using Compressive Signal Processing
Karsten Fyhn,Thomas Arildsen,Torben Larsen,S?ren Holdt Jensen
Mathematics , 2011,
Abstract: We show that to lower the sampling rate in a spread spectrum communication system using Direct Sequence Spread Spectrum (DSSS), compressive signal processing can be applied to demodulate the received signal. This may lead to a decrease in the power consumption or the manufacturing price of wireless receivers using spread spectrum technology. The main novelty of this paper is the discovery that in spread spectrum systems it is possible to apply compressive sensing with a much simpler hardware architecture than in other systems, making the implementation both simpler and more energy efficient. Our theoretical work is exemplified with a numerical experiment using the IEEE 802.15.4 standard's 2.4 GHz band specification. The numerical results support our theoretical findings and indicate that compressive sensing may be used successfully in spread spectrum communication systems. The results obtained here may also be applicable in other spread spectrum technologies, such as Code Division Multiple Access (CDMA) systems.
Reliable Identification of RFID Tags Using Multiple Independent Reader Sessions
Rasmus Jacobsen,Karsten Fyhn Nielsen,Petar Popovski,Torben Larsen
Mathematics , 2009,
Abstract: Radio Frequency Identification (RFID) systems are gaining momentum in various applications of logistics, inventory, etc. A generic problem in such systems is to ensure that the RFID readers can reliably read a set of RFID tags, such that the probability of missing tags stays below an acceptable value. A tag may be missing (left unread) due to errors in the communication link towards the reader e.g. due to obstacles in the radio path. The present paper proposes techniques that use multiple reader sessions, during which the system of readers obtains a running estimate of the probability to have at least one tag missing. Based on such an estimate, it is decided whether an additional reader session is required. Two methods are proposed, they rely on the statistical independence of the tag reading errors across different reader sessions, which is a plausible assumption when e.g. each reader session is executed on different readers. The first method uses statistical relationships that are valid when the reader sessions are independent. The second method is obtained by modifying an existing capture-recapture estimator. The results show that, when the reader sessions are independent, the proposed mechanisms provide a good approximation to the probability of missing tags, such that the number of reader sessions made, meets the target specification. If the assumption of independence is violated, the estimators are still useful, but they should be corrected by a margin of additional reader sessions to ensure that the target probability of missing tags is met.
Compressive Parameter Estimation for Sparse Translation-Invariant Signals Using Polar Interpolation
Karsten Fyhn,Marco F. Duarte,S?ren Holdt Jensen
Mathematics , 2013,
Abstract: We propose new compressive parameter estimation algorithms that make use of polar interpolation to improve the estimator precision. Our work extends previous approaches involving polar interpolation for compressive parameter estimation in two aspects: (i) we extend the formulation from real non-negative amplitude parameters to arbitrary complex ones, and (ii) we allow for mismatch between the manifold described by the parameters and its polar approximation. To quantify the improvements afforded by the proposed extensions, we evaluate six algorithms for estimation of parameters in sparse translation-invariant signals, exemplified with the time delay estimation problem. The evaluation is based on three performance metrics: estimator precision, sampling rate and computational complexity. We use compressive sensing with all the algorithms to lower the necessary sampling rate and show that it is still possible to attain good estimation precision and keep the computational complexity low. Our numerical experiments show that the proposed algorithms outperform existing approaches that either leverage polynomial interpolation or are based on a conversion to a frequency-estimation problem followed by a super-resolution algorithm. The algorithms studied here provide various tradeoffs between computational complexity, estimation precision, and necessary sampling rate. The work shows that compressive sensing for the class of sparse translation-invariant signals allows for a decrease in sampling rate and that the use of polar interpolation increases the estimation precision.
Compressive Time Delay Estimation Using Interpolation
Karsten Fyhn,Marco F. Duarte,S?ren Holdt Jensen
Computer Science , 2013,
Abstract: Time delay estimation has long been an active area of research. In this work, we show that compressive sensing with interpolation may be used to achieve good estimation precision while lowering the sampling frequency. We propose an Interpolating Band-Excluded Orthogonal Matching Pursuit algorithm that uses one of two interpolation functions to estimate the time delay parameter. The numerical results show that interpolation improves estimation precision and that compressive sensing provides an elegant tradeoff that may lower the required sampling frequency while still attaining a desired estimation performance.
Review of Survey activities 2009: Vietnamese sedimentary basins: geological evolution and petroleum potential
Fyhn, Michael B.W.,Petersen, Henrik I.,Mathiesen, Anders,Nielsen, Lars H.
Geological Survey of Denmark and Greenland Bulletin , 2010,
Abstract:
Compressive Sensing for Spread Spectrum Receivers
Karsten Fyhn,Tobias Lindstr?m Jensen,Torben Larsen,S?ren Holdt Jensen
Mathematics , 2013,
Abstract: With the advent of ubiquitous computing there are two design parameters of wireless communication devices that become very important power: efficiency and production cost. Compressive sensing enables the receiver in such devices to sample below the Shannon-Nyquist sampling rate, which may lead to a decrease in the two design parameters. This paper investigates the use of Compressive Sensing (CS) in a general Code Division Multiple Access (CDMA) receiver. We show that when using spread spectrum codes in the signal domain, the CS measurement matrix may be simplified. This measurement scheme, named Compressive Spread Spectrum (CSS), allows for a simple, effective receiver design. Furthermore, we numerically evaluate the proposed receiver in terms of bit error rate under different signal to noise ratio conditions and compare it with other receiver structures. These numerical experiments show that though the bit error rate performance is degraded by the subsampling in the CS-enabled receivers, this may be remedied by including quantization in the receiver model. We also study the computational complexity of the proposed receiver design under different sparsity and measurement ratios. Our work shows that it is possible to subsample a CDMA signal using CSS and that in one example the CSS receiver outperforms the classical receiver.
Fast and Power Efficient Sensor Arbitration: Physical Layer Collision Recovery of Passive RFID Tags
Karsten Fyhn,Rasmus M. Jacobsen,Petar Popovski,Anna Scaglione,Torben Larsen
Computer Science , 2010,
Abstract: This work concerns physical layer collision recovery for cheap sensors with allowed variations in frequency and delay of their communications. The work is presented as a generic, communication theoretic framework and demonstrated using UHF RFID tag technology. Previous work in this area has not provided recovery for more than two tags, which is shown to be possible in this work. Also presented is a novel mathematical model of the tag signal, incorporating the allowed variations in frequency and delay. The main motivation is seen in the observation that random variations in frequency and delay make the collided signals of different tags separable. The collision recovery is done by estimating the sensor specific variation in frequency and delay and using these estimates in a successive interference cancellation algorithm and a maximum likelihood sequence decoder, to iteratively reconstruct a sensor signal and remove it from the received signal. Numerical simulations show that the estimates and proposed algorithm are effective in recovering collisions. The proposed algorithm is then incorporated into a numerical simulation of the Qprotocol for UHF RFID tags and is shown to be effective in providing fast and power efficient sensor arbitration.
Review of Survey activities 2011: The Cenozoic Song Hong and Beibuwan Basins, Vietnam
Fyhn, M.B.W.,Petersen, H.I.,Nielsen, L.H.,Giang, T.C.
Geological Survey of Denmark and Greenland Bulletin , 2012,
Abstract:
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