1:00, SPCOM-P1.1
MODIFIED CHANNEL SUBSPACE METHOD FOR IDENTIFICATION OF SIMO FIR CHANNELS DRIVEN BY A TRAILING ZERO FILTER BANK PRECODER
H. BALOCH, J. MANTON, Y. HUA
A modification of Moulines' blind second order statistical Channel Subspace approach is proposed for the identification of single input multiple output finite impulse response channels. The modification exploits the transmitter redundancy introduced by a trailing zero filter bank precoder. The method is shown to be robust to common zeros and channel order over-estimation errors.

1:00, SPCOM-P1.2
A FREQUENCY DOMAIN METHOD FOR CHANNEL ESTIMATION IN MULTIRATE COMMUNICATION SYSTEMS
H. YAN, S. ROY
In this paper, a new frequency domain approach towards blind channel identification for multirate communication systems is described. Users are first separated based on different cyclic frequencies corresponding to their respective symbol rates, thereby resulting in a single-user (blind) identification scenario. The algorithm proposed in [2] is then used to estimate the channels for each rate. Computer simulations demonstrate the effectiveness of our method.

1:00, SPCOM-P1.3
ON BLIND (NON)IDENTIFIABILITY OF DISPERSIVE BANDLIMITED CHANNELS
H. GAZZAH, P. REGALIA, J. DELMAS
We study the asymptotic behavior of the smallest singular value of the Single Input Multiple Output (SIMO) channel filtering matrix. We prove that this can be expressed in terms of the sub-channel transfer functions. We apply this result to study the identifiability of bandlimited channels from their (estimated) second order statistics (SOS). We prove, and verify through examples, that SOS based algorithms are unable to identify frequency selective channels regardless of the assumed channel order.

1:00, SPCOM-P1.4
A MINIMUM MEAN-SQUARED ERROR INTERPRETATION OF RESIDUAL ISI CHANNEL SHORTENING FOR DISCRETE MULTITONE TRANSCEIVERS
D. DALY, C. HENEGHAN, A. FAGAN
Melsa et al. presented a channel shortening technique for Discrete Multitone transceivers that reduces Intersymbol Interference (ISI) by forcing the effective channel’s impulse response to lie within a window of v+1 consecutive samples. Arslan et al. claim that although this method is intuitive, no previous study has been made on its optimality. They comment on its optimality by simulation. In this paper it is demonstrated that Melsa’s approach is in fact theoretically equivalent to a minimum mean-squared error (MMSE) solution to the channel-shortening problem. As a corollary to this we are afforded an insight into MMSE channel shortening as originally proposed by Falconer and Magee . Previously, it has not been intuitive as to why the Desired Impulse Response (DIR) should be made adaptive in this approach. Our result demonstrates that allowing DIR adaptation achieves a minimisation of the effective impulse response energy outside the desired window of v samples.

1:00, SPCOM-P1.5
PREFILTERED BLIND EQUALIZATION: HOW TO FULLY BENEFIT FROM SPATIO-TEMPORAL DIVERSITY?
A. DE BAYNAST, I. FIJALKOW
We propose a new structure for blind equalization with spatio-temporal diversity at the receiver (SIMO system). This structure is derived from the Wiener filter. It is composed by a prefilter deduced from the data spectral density (no blind criterion is needed) and a FIR filter, independent from the noise level, to be obtained blindly. The new prefilter is robust to a total lack of effective diversity and benefits from any available diversity. Simulations show that this new blind equalizer performs similarly to the Wiener filter even with a very small amount of data.

1:00, SPCOM-P1.6
BLIND EQUALIZATION OF NONLINEAR CHANNELS FROM SECOND ORDER STATISTICS USING PRECODING AND CHANNEL DIVERSITY
R. LOPEZ-VALCARCE, X. SONG, S. DASGUPTA
This paper considers the blind equalization problem for nonlinear channels of Volterra type excited by real iid symbols. Previous work has shown that under the right conditions the equalizers can be found from the second order statistics of the channel output as long as the number of subchannels exceeds the number of kernels. In order to alleviate this requirement, we consider the use of a simple precoding device previous to transmission which provides a trade-off between effective data rate and number of subchannels required. Necessary and sufficient conditions for blind equalizability under this scheme are given, and an algorithm for the computation of the equalizers is presented.

1:00, SPCOM-P1.7
MIMO FIR EQUALIZERS AND ORDERS
R. RAJAGOPAL, L. POTTER
A necessary and sufficient condition is given for the existence of a polynomial left inverse for a polynomial (FIR) system. Additionally, random systems are defined, and a sufficient condition is given for almost sure existence of a polynomial inverse. The two results extend previous work in single-input, multiple-output systems to the case of multiple input systems and to functions of several variables. An algorithm to compute minimal order equalizers is also presented. Corollaries describe calibration of polarimetric, wide-band radar imagery.

1:00, SPCOM-P1.8
TRANSFORM DOMAIN QUASI-NEWTON ALGORITHMS FOR ADAPTIVE EQUALIZATION IN BURST TRANSMISSION SYSTEMS
K. BERBERIDIS, S. RANTOS, J. PALICOT
In this paper two new adaptive equalizers are proposed which belong to the quasi-Newton (QN) algorithmic family. The first algorithm is a Linear Equalizer (LE) and the second one is a Decision Feedback Equalizer (DFE). In the LE case the involved inverse Hessian matrix is approximated by a proper expansion consisting of powers of a Toeplitz matrix. Due to this formulation the algorithm can be efficiently implemented in the transform domain (TD) using FFT. The same idea is applied to the Feedforward part of the DFE. The derived algorithms enjoy the advantages of QN algorithms, that is, they exhibit faster convergence than their stochastic gradient counterparts and less computational complexity as compared to other Newton-type algorithms. These advantages are further enhanced due to the TD implementation.

1:00, SPCOM-P1.9
CLOSED FORM EXPRESSION OF EMSE FOR BUSSGANG EQUALIZATION WITH SPATIO-TEMPORAL DIVERSITY
A. TOUZNI, T. ENDRES, R. CASAS, C. STROLLE
Bussgang algorithms are a class of simple stochastic gradient type solutions for blind channel equalization. In this contribution we investigate the degradation of performance in the source estimation resulting from the stochastic jitter around the stationary points of Bussgang algorithms (which correspond to the equalizers of the channel). More precisely, we derive a closed form approximation of the Excess Mean Square Error (EMSE) defined as the variance of the jitter which depends on the effects of the channel characteristics, the source distribution and the non-linearity used in the update equation. The analysis is performed in a context of spatio-temporal channel diversity involving a single-input/ multiple outputs data model.

1:00, SPCOM-P1.10
A CONSIDERATION ON THE BLIND ESTIMATION OF SINGLE-INPUT DOUBLE-OUTPUT SYSTEM USING ORTHOGONAL DIRECT SUM DECOMPOSITION OF RECEIVED SIGNAL SPACE
N. TANABE, T. FURUKAWA, S. TUSJII
The subspace methods with second-order statistics based on PCA basically need to calculate the eigen-values and the eigen-vectors of the autocorrelation matrix of the received signal. However, the calculation of the eigen-values and the eigen-vectors of the matrix requires much computational complexity. In this paper, we propose a new algorithm based on PCA without solving the eigen-values and the eigen-vectors of the matrix. Moreover, we perform the proposed method under the condition that noise-variance is known, but we confirmed that the proposed method is effective to a certain degree when noise-variance is unknown. We show the effectiveness of the proposed method by numerical examples.