HomeChair: Michail K. Tsatsanis, Stevens Inst. of Tech., USA
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David J. Gesbert, Stanford University (U.S.A.)
Joakim Sorelius, Uppsala University (Sweden)
Arogyaswami J. Paulraj, Stanford University (U.S.A.)
The recovery of code-division multiple access (CDMA) information signals in a frequency selective fading channel is a problem of great theoretical and practical interest. This paper addresses the estimation of an optimal (within the class of linear detectors) multi-user CDMA receiver. A novel approach is introduced that enables the estimation of the minimum mean-square error (MMSE) detector in a blind setting. The MMSE detector is obtained through a double subspace projection that exploits the subspace structure associated with both the code of the desired user and the estimated signal subspace of the covariance matrix for the observed signals. The technique allows for interference rejection without requiring the knowledge of the codes for the interferers.
ic982336.pdf (From Postscript)
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João MM. F. Xavier, Instituto Superior Técnico (Portugal)
Victor A.N. Barroso, Instituto Superior Técnico (Portugal)
José M.F. Moura, CMU (U.S.A.)
We present a closed-form algorithm for blind identification of multiple-input/multiple-output (MIMO) finite-impulse response (FIR) systems driven by digital sources. The algorithm is based on second order statistics and yields an asymptotically exact estimate of the MIMO channel. We assign distinct spectral signatures to each user through transmitter correlative filters, and exploits this spectral asymmetry to derive the closed-form solution. Simulation results illustrate the good performance of the proposed approach. We compare the mean square error (MSE) of the MIMO channel estimate against the Cramer-Rao bound, and assess the algorithm capability in rejecting inter-user crosstalk interference.
ic981970.pdf (From Postscript) TOP
Xiaodong Wang, Princeton University (U.S.A.)
H. Vincent Poor, Princeton University (U.S.A.)
In many wireless systems where multiuser detection techniques may be applied, the ambient channel noise is known through experimental measurements to be decidedly non-Gaussian, due largely to impulsive phenomena. The performanceof many multiuser detectors can degrade substantially in the presence of such impulsive ambient noise. In this paper, a blind adaptive robust multiuser detection technique is developed for combating both multiple-access interference and impulsive noise in CDMA communication systems. This technique is nonlinear in nature and it is based on the signal subspace tracking method and the $M$-estimation method for robust regression. It is seen that the proposed technique offers significant performance gain over linear adaptive multiuser detectors in impulsive noise, with little attendant increase in computational complexity.
ic981325.pdf (From Postscript) TOP
Yung-Fang Chen, Purdue University (U.S.A.)
Michael D. Zoltowski, Purdue University (U.S.A.)
We previously presented a blind 2D RAKE receiver for CDMA that cancels strong multi-user access interference and optimally combines multipath. The weight vector yielding the optimum signal to interference plus noise ratio for bit decisions is the ``largest"" generalized eigenvector of the spatio-frequency (spatio-temporal) correlation matrix pencil. However, the eigen-analysis based algorithm is on the order of O(N3) computational complexity and the resulting spatio-frequency (spatio-temporal) correlation matrix pencil is of large dimension. This detracts from the real-time applicability of that scheme. A blind 2-D RAKE receiver is thus presented based on an RLS-type space-time adaptive filtering scheme which offers O(N2) computational complexity and competitive performance. The applicability of the scheme to the IS-95 uplink is also addressed as in a decision directed fashion.
ic982191.pdf (From Postscript) TOP
Zhi Ding, Auburn University (U.S.A.)
Iain B Collings, Melbourne University (Australia)
Ruey-wen Liu, University of Notre Dame (U.S.A.)
Blind channel equalization has recently been a very active research topic due to its potential application in mobile communications and digital TV systems. In this paper, we present a new blind zero-forcing equalizer that utilizes second order statistics from the multi-channel configuration. The algorithm is simple and relies only on nullspace decomposition. It can actively select the desired delay of the equalizer output signal. The performance of this new algorithm is demonstrated through simulation examples.
ic981756.pdf (From Postscript) TOP
Alex Stéphenne, INRS-Telecommunications (Canada)
Benoît Champagne, INRS-Telecommunications (Canada)
In this paper, the blind estimation of wireless CDMA receiver coefficients from the second order statistics of the signals is considered. Although many algorithms have been proposed so far, their performance analysis has always been carried out assuming perfect receiver coefficients estimation and/or under time-invariant conditions. In this article, we present some decision-directed blind algorithms and use a time-varying vector channel simulator to compare their performance with those of many recently proposed algorithms. It is shown that decision-directed chip-level algorithms can operate without the use of training sequences to avoid catastrophic error propagation, and that one should not expect an increase in performance from using least squares instead of least-mean-square. Furthermore the unpracticability of the bit-level algorithm and of the least significant algorithm under time varying environment is outlined. The performance of the principal component (Stanford) algorithm is also studied.
ic981814.pdf (From Postscript) TOP
Jaouhar Ayadi, Institut EURECOM (France)
Elisabeth De Carvalho, Institut EURECOM (France)
Dirk T.M. Slock, Institut EURECOM (France)
We investigate Maximum Likelihood (ML) methods for blind and semi-blind estimation of multiple FIR channels. Two blind Deterministic ML (DML) strategies are presented. In the first one, we propose to modify the Iterative Quadratic ML (IQML) algorithm in order to ""denoise"" it and hence obtain consistent channel estimates. The second strategy, called Pseudo-Quadratic ML (PQML), is naturally asymptotically denoised. Links between these two approaches are established and their global convergence is proved. Furthermore, we propose semi-blind ML techniques combining PQML with two different training sequence estimation methods and compare their performance. These semi-blind techniques, exploiting the presence of known symbols, outperform their blind version. They also allow channel estimation in situations where blind and training sequence methods fail separately. Simulations are presented to demonstrate the performance of all the proposed algorithms, and comparisons between them are discussed in a blind and/or semi-blind context.
ic982479.pdf (From Postscript) TOP
Shang-Chieh Liu, University of Maryland (U.S.A.)
Evaggelos Geraniotis, University of Maryland (U.S.A.)
In this paper, we present a blindly adaptive beamforming algorithm which is based on the second order interference estimation to maximize the received SINR. Using the desired signature code and the orthogonal to it code, a new code filter is introduced to decompose the receiving signals into two part : desired information and interference. The above method motivates us to develop the QR-decomposition based dominant eigen mode search (QRD-DMS) algorithm which is more numerically stable than the DMS one. The corresponding wavefront systolic architecture is also proposed for the VLSI implementations. Compare to the families of minimum mean square error (MMSE) algorithms which need training sequences, we have completed the maximum SINR families, as shown in Table 1, QRD-DMS method which not only blindly updates the beamforming weights and converges as fast as the QRD-RLS method.
ic981505.pdf (From Postscript) TOP