The Experts below are selected from a list of 92250 Experts worldwide ranked by ideXlab platform
Weichieh Huang - One of the best experts on this subject based on the ideXlab platform.
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semi blind channel estimation using superimposed training sequences with Constant Magnitude in dual domain for ofdm systems
Vehicular Technology Conference, 2006Co-Authors: Weichieh HuangAbstract:A superimposed training scheme is proposed for channel estimation in OFDM systems. The generalized chirp-like (GCL) sequence is adopted since it has a Constant Magnitude in both the time domain and the frequency domain. Although the derived channel estimator has a slightly worse performance since the unknown data contributes extra noise, the effective data throughput is substantially increased. In addition, the proposed scheme is shown to have a much better peak-to-average power ratio (PAPR) because the added GCL sequence has a Constant Magnitude in the time domain.
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VTC Spring - Semi-Blind Channel Estimation Using Superimposed Training Sequences with Constant Magnitude in Dual Domain for OFDM Systems
2006 IEEE 63rd Vehicular Technology Conference, 1Co-Authors: Weichieh HuangAbstract:A superimposed training scheme is proposed for channel estimation in OFDM systems. The generalized chirp-like (GCL) sequence is adopted since it has a Constant Magnitude in both the time domain and the frequency domain. Although the derived channel estimator has a slightly worse performance since the unknown data contributes extra noise, the effective data throughput is substantially increased. In addition, the proposed scheme is shown to have a much better peak-to-average power ratio (PAPR) because the added GCL sequence has a Constant Magnitude in the time domain.
T I Laakso - One of the best experts on this subject based on the ideXlab platform.
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closed form design of digital fractional delay filters with Constant Magnitude and variable delay
European Signal Processing Conference, 2005Co-Authors: Xiaojing Zhang, Martin Makundi, T I LaaksoAbstract:In most approximation techniques for implementing a variable fractional delay, like Lagrange interpolation, the Magnitude response varies considerably with the delay. Instead, it would be desirable to keep the Magnitude response the same for all delay values. In this paper, we propose a novel method for optimizing the parameters of the least-squared error spline transition band fractional delay FIR design to achieve good delay approximation with delay-independent Magnitude response.
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EUSIPCO - Closed-form design of digital fractional-delay filters with Constant Magnitude and variable delay
2005Co-Authors: Xiaojing Zhang, Martin Makundi, T I LaaksoAbstract:In most approximation techniques for implementing a variable fractional delay, like Lagrange interpolation, the Magnitude response varies considerably with the delay. Instead, it would be desirable to keep the Magnitude response the same for all delay values. In this paper, we propose a novel method for optimizing the parameters of the least-squared error spline transition band fractional delay FIR design to achieve good delay approximation with delay-independent Magnitude response.
Xiaojing Zhang - One of the best experts on this subject based on the ideXlab platform.
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closed form design of digital fractional delay filters with Constant Magnitude and variable delay
European Signal Processing Conference, 2005Co-Authors: Xiaojing Zhang, Martin Makundi, T I LaaksoAbstract:In most approximation techniques for implementing a variable fractional delay, like Lagrange interpolation, the Magnitude response varies considerably with the delay. Instead, it would be desirable to keep the Magnitude response the same for all delay values. In this paper, we propose a novel method for optimizing the parameters of the least-squared error spline transition band fractional delay FIR design to achieve good delay approximation with delay-independent Magnitude response.
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EUSIPCO - Closed-form design of digital fractional-delay filters with Constant Magnitude and variable delay
2005Co-Authors: Xiaojing Zhang, Martin Makundi, T I LaaksoAbstract:In most approximation techniques for implementing a variable fractional delay, like Lagrange interpolation, the Magnitude response varies considerably with the delay. Instead, it would be desirable to keep the Magnitude response the same for all delay values. In this paper, we propose a novel method for optimizing the parameters of the least-squared error spline transition band fractional delay FIR design to achieve good delay approximation with delay-independent Magnitude response.
Martin Makundi - One of the best experts on this subject based on the ideXlab platform.
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closed form design of digital fractional delay filters with Constant Magnitude and variable delay
European Signal Processing Conference, 2005Co-Authors: Xiaojing Zhang, Martin Makundi, T I LaaksoAbstract:In most approximation techniques for implementing a variable fractional delay, like Lagrange interpolation, the Magnitude response varies considerably with the delay. Instead, it would be desirable to keep the Magnitude response the same for all delay values. In this paper, we propose a novel method for optimizing the parameters of the least-squared error spline transition band fractional delay FIR design to achieve good delay approximation with delay-independent Magnitude response.
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EUSIPCO - Closed-form design of digital fractional-delay filters with Constant Magnitude and variable delay
2005Co-Authors: Xiaojing Zhang, Martin Makundi, T I LaaksoAbstract:In most approximation techniques for implementing a variable fractional delay, like Lagrange interpolation, the Magnitude response varies considerably with the delay. Instead, it would be desirable to keep the Magnitude response the same for all delay values. In this paper, we propose a novel method for optimizing the parameters of the least-squared error spline transition band fractional delay FIR design to achieve good delay approximation with delay-independent Magnitude response.
Mohammad Mahdi Nayebi - One of the best experts on this subject based on the ideXlab platform.
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Invariant activity detection of a Constant Magnitude signal with unknown parameters in white Gaussian noise
IET Communications, 2009Co-Authors: Mostafa Derakhtian, Aliakbar Tadaion, Saeed Gazor, Mohammad Mahdi NayebiAbstract:The authors propose invariant tests for the detection of a complex signal with unknown Constant amplitude and unknown phase variation in additive white Gaussian noise (AWGN). The authors show that in this problem, the uniformly most powerful invariant (UMPI) detector does exist only if the number of samples N is two. For more than two samples N≥3, the authors derive the most powerful invariant (MPI) detector in known signal-to-noise ratio (SNR) and use its performance as the upper bound benchmark for any invariant test. In addition, the authors derive the generalised likelihood ratio (GLR) detector and evaluate its performance against the MPI performance bound. This detector is very simple and represents the ratio of the L1-norm to the L2-norm of the data. Simulation results illustrate the close performances of the two detectors even at low SNRs, whereas in contrast to the MPI test the SNR is not required in the proposed GLR test. In order to understand why the knowledge of SNR is not so important in this detection problem, the authors also derive the GLR test for the case of known SNR. Interestingly, the resulting GLR detector (derived for the case of known SNR) turns out to be equivalent to the one derived for unknown SNR, i.e. a knowledge of the SNR is not used in any of the GLR tests. This reveals why the knowledge of the SNR is not so useful in this detection problem.
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Invariant Detection of a Constant Magnitude Signal with Unknown Parameters in White Gaussian Noise
2007 IEEE International Conference on Signal Processing and Communications, 2007Co-Authors: Aliakbar Tadaion, Mostafa Derakhtian, Saeed Gazor, Mohammad Mahdi NayebiAbstract:In this paper, we use invariant tests for the detection of a complex signal with unknown phase variation and unknown amplitude in additive white Gaussian noise (AWGN). We show that in this problem, the uniformly most powerful invariant (UMPI) detector exists only if the signal-to-noise-ratio (SNR) is known. We derive the UMPI detector in known SNR and use it as the upper performance bound for any invariant test. In addition, we derive the generalized likelihood ratio (GLR) detector and evaluate its performance against the UMPI performance bound. We show that the GLR detector asymptotically approaches the UMPI test in large SNRs. Simulation results illustrate the close performances of the two detectors even at low SNRs, while in contrast of the UMPI test the SNR is unknown in the proposed GLR test. In order to understand, why the knowledge of SNR is not so important in this detection problem, we also derive the GLR test for the case of known SNR. Interestingly, the resulting GLR detector (derived for the case of known SNR) turns out equivalent with the one derived for unknown SNR, i.e., the knowledge of the SNR is not used in any of GLR tests. This reveals why the knowledge of the SNR is not so useful in this detection problem.