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Tsung-Hsien Liu
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ABSTRACT: We analyze the principal component combining with differential detection (PCC-DD) with weight estimation for the demodulation of DPSK signals in diversity systems. The estimated weight vector is considered to be the principal component of the exponentially weighted sample correlation matrix of the signals at diversity channel outputs. We arrive at closed form expressions for the approximate bit error rate (BER) for the scenario where channel gains are fixed, and the approximate average BER for the scenario where channel gains are independent identically Rayleigh distributed. The analysis provides accurate BER approximation, and is justified by the results from computer simulations. We also arrive at a rule of thumb about the value of the forgetting factor of the exponentially weighted sample correlation matrix should be selected for PCC-DD to yield good performance under time varying Rayleigh fading channels
IEEE Transactions on Wireless Communications 04/2007; · 2.59 Impact Factor
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European Transactions on Telecommunications. 01/2006; 17:461-471.
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Tsung-Hsien Liu
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ABSTRACT: We propose a principal component combining with differential detection (PCC-DD) for the demodulation of DPSK signals over a slow fading DSSS system. Our PCC-DD does not need the pilot signal and can blindly estimate the channel information. When the symbol period is much larger than the channel delay spread, our PCC-DD is as optimal as the maximal ratio combining with differential detection (MRC-DD) in generating combining output with maximal SNR. Our analysis for the scenario when the symbol period is comparable to the channel delay spread also agrees with the results from simulations. Adaptive implementation of our PCC-DD is demonstrated to be of low computational complexity.
Communications, 2005. ICC 2005. 2005 IEEE International Conference on; 06/2005
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Tsung-Hsien Liu
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ABSTRACT: Our proposed orthogonal decision feedback detector (ODFD) contains an orthogonal feedforward filter and a decision feedback structure. Compared with the decorrelating decision feedback detector (DDFD), our QR-factorization-based ODFD is computationally more efficient in dynamically updating the feedforward and feedback filter pairs. This feature is beneficial when the number of users in a system changes frequently. Using the Gaussian approximation, which was used to compute the approximate bit-error probabilities (BEPs) of multiusers for the successive interference canceller (SIC), we calculate the approximate BEPs of multiusers for the DDFD and our ODFD. The Gaussian approximation leads to good approximate BEPs for DDFD and to fine approximate BEPs for ODFD, but to poor approximate BEPs for SIC. The accuracy of these approximate BEPs is also justified by the results from Monte Carlo simulations.
IEEE Transactions on Vehicular Technology 10/2004; · 1.92 Impact Factor
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Tsung-Hsien Liu
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ABSTRACT: We propose a new blind multiuser detector for frequency-selective multipath channels. Our new linearly constrained minimum variance (LCMV) RAKE receiver is an enhancement to the previously published decorrelating RAKE (D-RAKE) receiver. Compared with the D-RAKE receiver, our LCMV-RAKE receiver processes full information of the desired user and is shown by simulations to provide lower bit-error rates. In some scenarios, our LCMV-RAKE receiver outperforms the minimum output energy detector by M.K. Tsatsanis and Z. Xu (see IEEE Trans. Sig. Processing, vol.46, p.3014-22, 1998). Adaptive implementation of our LCMV-RAKE receiver is demonstrated to be feasible.
IEEE Transactions on Communications 11/2003; · 1.68 Impact Factor
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ABSTRACT: In this paper, we study blind channel estimation in code division multiple access systems from array signal processing perspective. As there are three direction-of-arrival estimation methods in array signal processing, we formulate three corresponding blind channel estimation methods in a framework, although some of which have already been reported. From our analysis and simulations, the constrained and subspace methods for blind channel estimation outperforms the conventional method. The conventional method is computationally more efficient, and is suitable for the scenario where only few users exist and where good power control is taken care of.
Personal, Indoor and Mobile Radio Communications, 2003. PIMRC 2003. 14th IEEE Proceedings on; 10/2003
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ABSTRACT: We propose several classes of fractional lower order moment
(FLOM)-based matrices that can be used with MUSIC to estimate the DOAs
of independent circular signals embedded in additive SαS
(symmetric α stable) noise (e.g., sea clutter). We run simulations
with different choices of the FLOM parameter p for our FLOM-based
matrices and conclude that when the noise is SαS with unknown
α≠2, FLOM-multiple signal classification (MUSIC) with p close
to unity yields good performance. The performance of FLOM-MUSIC and
robust covariation-based (ROC)-MUSIC are similar. Three scenarios that
contain circular signals (phase modulation (PM), circularly symmetrical
Gaussian, and quaternary phase-shift keying (QPSK)) and one scenario
that contains noncircular signals (binary phase-shift keying (BPSK)),
all embedded in the same SαS noise, are tested. These simulation
results reveal that the scenario containing BPSK signals leads to poor
performance, indicating that FLOM-MUSIC is presently limited to circular
signals
IEEE Transactions on Signal Processing 09/2001; · 2.63 Impact Factor
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Tsung-Hsien Liu
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ABSTRACT: Our proposed orthogonal decision feedback detector (ODFD) contains
an orthogonal feedforward filter and allows decision feedback. While the
decorrelating decision feedback detector (DDFD) is motivated by the
Cholesky factorization of the correlation matrix of signature sequences,
our ODFD is motivated by the QR-factorization of the same correlation
matrix. In the absence of additive noise, ODFD is robust to multiple
access interference. We observe from simulations that ODFD outperforms
the decorrelating detector, due to the decision feedback, but is out
performed by the DDFD. While the flop counts and bit error rate analysis
tends to exaggerate for Cholesky factorization based methods such as the
DDFD, the QR approach such as the ODFD is comparable in efficiency if
memory traffic and vectorization overheads are considered
Communications, 2001. ICC 2001. IEEE International Conference on; 02/2001
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Tsung-Hsien Liu
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ABSTRACT: Using the Gaussian approximation, we calculate the approximate bit
error probabilities (BEPs) or three multiusers. The accuracy of
approximate BEPs for successive interference canceller (SIC),
decorrelating decision feedback detector (DDFD), and orthogonal decision
feedback detector (ODFD) depends on two factors. The first factor is
whether the desired component at the input to the threshold is
correlated with undesired component. The second factor is whether the
approximate variance of the Gaussian undesired component contains
non-zero covariance terms. The Gaussian approximation leads to good
approximate BEPs for DDFD, to fair approximate BEPs for ODFD, but to
poor approximate BEPs for SIC. The accuracy of these approximate BEPs is
also justified by the results from Monte Carlo simulations
Global Telecommunications Conference, 2001. GLOBECOM '01. IEEE; 02/2001
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ABSTRACT: For pt.IV see ibid., vol.45, p.2265-76 (1997). Virtual-ESPRIT
(VESPA) imposes a slight constraint on the array, i.e., only a pair of
identical sensors are required. We follow the classical procedure to
define the sensitivity of VESPA with respect to each model parameter and
derive closed forms for the sensitivity formulas. We justify our
derivations by comparing the theoretical formulas with the results from
Monte Carlo simulations. Additionally, we demonstrate, by simulations,
that VESPA is more robust to model mismatches than ESPRIT in most
situations
IEEE Transactions on Signal Processing 04/1999; · 2.63 Impact Factor
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ABSTRACT: We present a gradient-based cumulant method to track the signal subspace in an array signal processing scenario. This method is combined with a non-adaptive singular value decomposition (SVD) and a non-adaptive eigenvalue decomposition (EVD) to yield an adaptive virtual-ESPRIT algorithm (VESPA) for target tracking. The resulting least-mean-squared VESPA (LMS-VESPA) is of complexity O(M<sup>2</sup>P). In addition to hardware saving, we demonstrate through simulations that, when the signals are closely spaced, block-adaptive ESPRIT suffers even from slight colored noise, and that when the SNR is poor whether the signals are close or not, LMS-VESPA is still robust to such noise
Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on; 12/1998
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ABSTRACT: An ESPRIT-based algorithm is proposed to estimate the azimuth and
elevation angles of multiple independent sources. The algorithm uses
cumulants and imposes no geometric constraint on the array. Only one
third of the hardware is needed for our algorithm as compared with
covariance-based two-dimensional (2-D) ESPRIT. Our algorithm can
estimate azimuth and elevation angles of M-1 sources using M sensors.
Simulation results show that for several array configurations, our
algorithm works well
IEEE Transactions on Signal Processing 08/1998; · 2.63 Impact Factor
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[show abstract]
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ABSTRACT: Virtual-ESPRIT (VESPA) imposes a slight constraint on the array i.e. only a pair of identical sensors are required. We follow the classical procedure to define the sensitivity of VESPA with respect to each model parameter, and derive closed forms for the sensitivity formulas. We justify our derivations by comparing the theoretical formulas with the results from Monte Carlo simulations. Additionally, we demonstrate, by simulations, that VESPA is more robust to model mismatches than ESPRIT in most situations
Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on; 12/1997
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ABSTRACT: An ESPRIT-based algorithm is proposed to estimate the azimuth and elevation angles of multiple independent sources. The algorithm uses cumulants and imposes no geometric constraint on the array. Only one third of the hardware is needed for our algorithm as compared with covariance-based 2-D ESPRIT. Our algorithm can estimate azimuth and elevation angles of M-1 sources using M sensors. Simulation results show that for several array configurations our algorithm works well.
Signals, Systems and Computers, 1996. Conference Record of the Thirtieth Asilomar Conference on; 12/1996
