Giacinto Gelli

Blind widely linear multiuser detection

Widely linear structures for multiuser detection of code division multiple-access signals are proposed, which jointly elaborate the received signal and its complex conjugate. Computer simulations show that the new structures significantly outperform the conventional linear ones, in terms of suppression capability of both wideband multiple-access and narrowband interference.

Compression of multispectral images by spectral classification and transform coding

This paper presents a new technique for the compression of multispectral images, which relies on the segmentation of the image into regions of approximately homogeneous land cover. The rationale behind this approach is that, within regions of the same land cover, the pixels have stationary statistics and are characterized by mostly linear dependency, contrary to what usually happens for unsegmented images. Therefore, by applying conventional transform coding techniques to homogeneous groups of pixels, the proposed algorithm is able to effectively exploit the statistical redundancy of the image, thereby improving the rate distortion performance. The proposed coding strategy consists of three main steps. First, each pixel is classified by vector quantizing its spectral response vector, so that both a reliable classification and a minimum distortion encoding of each vector are obtained. Then, the classification map is entropy encoded and sent as side information, Finally, the residual vectors are grouped according to their classes and undergo Karhunen-Loeve transforming in the spectral domain and discrete cosine transforming in the spatial domain. Numerical experiments on a six-band thematic mapper image show that the proposed technique outperforms the conventional transform coding technique by 1 to 2 dB at all rates of interest.

Cyclostationarity-based filtering for narrowband interference suppression in direct-sequence spread-spectrum systems

This paper addresses the problem of narrowband interference suppression in direct-sequence spread-spectrum (DS/SS) techniques, which have been adopted to implement code division multiple access (CDMA) systems for wireless mobile communications. The theory of cyclic Wiener filtering, based on the cyclostationarity assumption for the signals involved in the reception problem, is applied to design single-channel adaptive frequency-shift filters which exploit both temporal and spectral correlation properties, i.e., the correlation between time- and frequency-shifted versions of the received signal. The numerical results show that receiving structures based on the proposed cyclostationarity-based interference suppression schemes largely outperform receivers that utilize conventional linear time-invariant suppressors, when they operate in highly contaminated interference environments.

Widely linear equalization and blind channel identification for interference-contaminated multicarrier systems

This work addresses the problem of designing efficient detection techniques for multicarrier transmission systems operating in the presence of narrowband interference (NBI). In this case, conventional linear receivers, such as the zero-forcing (ZF) or the minimum-mean square error (MMSE) ones, usually perform poorly since they are not capable of suppressing satisfactorily the NBI. To synthesize interference-resistant detection algorithms, we resort to widely linear (WL) filtering, which allows one to exploit the noncircularity property of the desired signal constellation by jointly processing the received signal and its complex-conjugate version. In particular, we synthesize new WL-ZF receivers for multicarrier systems, which mitigate, in the minimum output-energy (MOE) sense, the NBI contribution at the receiver output, without requiring knowledge of the NBI statistics. By exploiting the noncircularity property, we also propose a new subspace-based blind channel identification algorithm and derive the channel identifiability condition. Blind identification can be performed satisfactorily also in the presence of NBI, requiring only an approximate rank determination of the NBI autocorrelation matrix. The performance analysis shows that the proposed MOE WL-ZF receiver, even when implemented blindly, assures a substantial improvement over the conventional linear ZF and MMSE ones, particularly when the NBI bandwidth is very small in comparison with the intercarrier spacing and the NBI is not exactly located on a subcarrier.

Subspace-based blind channel identification of SISO-FIR systems with improper random inputs

In this paper, we consider the problem of blindly estimating the impulse response of a nonminimum phase single-input single-output channel, by resorting only to the second-order statistics (SOS) of the channel output. On the basis of a general treatment of the problem, we show that a SOS-based subspace procedure can be applied to the problem at hand if the transmitted signal is an improper process, exhibiting some additional properties. After characterizing and discussing these properties, we show that they are exhibited by many improper digital modulation schemes of practical interest. Moreover, based on our unifying framework, we devise subspace-based algorithms for blind channel identification, by addressing in particular the related identifiability issues. Finally, the theoretical expression of the mean-squared error of the channel estimate is derived, and numerical simulations are carried out for its validation and for comparing the performance of the proposed algorithm with that of a conventional subspace-based method.

Widely Linear Versus Linear Blind Multiuser Detection With Subspace-Based Channel Estimation: Finite Sample-Size Effects

In a recent paper [A. S. Cacciapuoti <i>et</i> <i>al.</i>, ldquoFinite-Sample Performance Analysis of Widely Linear Multiuser Receivers in DS-CDMA Systems, IEEE Transactions on Signal Processing, vol. 56, no. 4, pp. 1572-1588, Apr. 2008], we presented the finite-sample theoretical performance comparison between linear (L) and widely linear (WL) minimum output-energy (MOE) receivers for direct-sequence code-division multiple-access (DS-CDMA) systems, worked out under the assumption that the channel impulse response of the desired user is exactly known. The main scope of this paper is to extend such an analysis, taking into account not only autocorrelation matrix (ACM) estimation effects, but also the accuracy of subspace-based blind channel estimation (CE). We aim to answer the two following questions: <i>Which</i> <i>of</i> <i>the</i> <i>two</i> <i>estimation</i> <i>processes</i> <i>(ACM</i> <i>or</i> <i>CE)</i> <i>is</i> <i>the</i> <i>main</i> <i>source</i> <i>of</i> <i>degradation</i> <i>when</i> <i>implementing</i> <i>the</i> <i>receivers</i> <i>on</i> <i>the</i> <i>basis</i> <i>of</i> <i>a</i> <i>finite</i> <i>sample-size?</i> <i>Compared</i> <i>with</i> <i>the</i> <i>L-MOE</i> <i>one,</i> <i>is</i> <i>the</i> <i>finite-sample</i> <i>WL-MOE</i> <i>receiver</i> <i>with</i> <i>blind</i> <i>CE</i> <i>capable</i> <i>of</i> <i>achieving</i> <i>the</i> <i>performance</i> <i>gains</i> <i>predicted</i> <i>by</i> <i>the</i> <i>theory?</i> To this goal, simple and easily interpretable formulas are developed for the signal-to-interference-plus-noise ratio (SINR) at the output of the L- and WL-MOE receivers with blind CE, when they are implemented using either the sample ACM or its eigendecomposition. In addition, the derived formulas, which are validated by simulations, allow one to recognize and discuss interesting tradeoffs between the main parameters of the DS-CDMA system.

Finite-Sample Performance Analysis of Widely Linear Multiuser Receivers for DS-CDMA Systems

This paper tackles the theoretical performance analysis of widely linear (WL) multiuser receivers for direct-sequence code-division multiple-access (DS-CDMA) systems, as well as their comparison with conventional linear (L) ones. In particular, receivers based on the minimum output-energy (MOE) criterion are considered, since they offer a good tradeoff between performance and complexity and, moreover, lend to some simplifications in the analysis. After comparing the ideal signal-to-interference-plus-noise-ratio (SINR) performances of the WL-MOE and L-MOE receivers, the paper establishes finite-sample performance results for two typical data-estimated implementations. Specifically, by adopting a first-order perturbative approach, the SINR degradation of the data-estimated WL-MOE receivers is accurately evaluated and compared with that of its linear counterpart. Simulation results are provided to validate and complement the theoretical analysis.

A Constrained Maximum-SINR NBI-Resistant Receiver for OFDM Systems

In this paper, with reference to the problem of joint equalization and narrowband interference (NBI) suppression in orthogonal frequency-division multiplexing (OFDM) systems, synthesis and analysis of both unconstrained and constrained optimum equalizers are carried out, based on the maximum signal-to-noise-plus-interference (SINR) criterion. Specifically, a comparative performance analysis is provided from a theoretical point of view, either when the second-order statistics (SOS) of the received data are exactly known at the receiver, or when they are estimated from a finite number of data samples. Relying on the results of this analysis, a three-stage constrained maximum-SINR equalizer is then proposed, which outperforms existing receivers and, in comparison with its unconstrained counterpart, exhibits a significantly stronger robustness against errors in the estimated SOS. Moreover, a computationally efficient adaptive implementation of the three-stage equalizer is derived, and in connection with it, a simple and effective NBI-resistant channel estimation algorithm is proposed. Finally, numerical simulations are performed that aim to validate the theoretical analysis carried out and compare the performances of the considered equalizers with those of existing approaches

Two-stage interference-resistant adaptive periodically time-varying CMA blind equalization

We consider the problem of blindly equalizing a digital communication signal distorted by a linear time-invariant channel and contaminated by severe co-channel or adjacent-channel digital interference under the assumption that the latter exhibits a different symbol rate from the desired signal. The proposed equalizer is composed of two stages that are both periodically time-varying (PTV) in order to better match the periodical statistics of the received signal. The first stage employs linear PTV filtering to mitigate interference, thus allowing the second stage, based on the constant modulus algorithm (CMA), to reliably recover the transmitted information symbols. Computer simulations confirm the effectiveness of the new approach, and comparisons with existing blind methods show that a significant performance gain can be attained.

Minimum-redundancy linear arrays for cyclostationarity-based source location

The problem of designing minimum-redundancy linear arrays (MRLAs) and appropriate augmentation techniques to be utilized with cyclostationarity-exploiting (cyclic) methods for source location is addressed. The MRLA geometries proposed in the literature for the conventional case, which apply equally well when the signals of interest exhibit cyclostationarity are not appropriate when they exhibit conjugate cyclostationarity. In this case, the problem of finding optimal MRLAs is restated as the problem of number theory that is commonly referred to as the postage stamp problem. Results of computer simulations show that in densely crowded environments, the use of cyclic methods with MRLA geometries and appropriate matrix augmentation techniques can offer a significant performance improvement on cyclic methods that do not resort to matrix augmentation techniques.