Combining blind equalization with constant modulus properties

Veen, A.‐J. van der; Trindade, A.

doi:10.1109/acssc.2000.911253

Cited by 4 publications

(3 citation statements)

References 11 publications

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“…In [6], Gesbert et al introduced the MIMO version of the MRE method. In 2000, J. van der Veen et al [7] proposed the combination of MRE with another blind algorithm, which is "Constant modulus" (CMA) for SIMO systems. [8] also used MRE method for SIMO models but reduced the complexity by computing only 2 instead of K equalizers as the original paper.…”

Section: Introductionmentioning

confidence: 99%

On the Semi-Blind Mutually Referenced Equalizers for MIMO Systems

Son,

Abed-Meraim,

Duy

et al. 2023

2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

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Minimizing training overhead in channel estimation is a crucial challenge in wireless communication systems. This paper presents an extension of the traditional blind algorithm, called "Mutually referenced equalizers" (MRE), specifically designed for MIMO systems. Additionally, we propose a novel semi-blind method, SB-MRE, which combines the benefits of pilot-based and MRE approaches to achieve enhanced performance while utilizing a reduced number of pilot symbols. Moreover, the SB-MRE algorithm helps to minimize complexity and training overhead and to remove the ambiguities inherent to blind processing. The simulation results demonstrated that SB-MRE outperforms other linear algorithms, i.e., MMSE, ZF, and MRE, in terms of training overhead symbols and complexity, thereby offering a promising solution to address the challenge of minimizing training overhead in channel estimation for wireless communication systems.

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Section: Introductionmentioning

confidence: 99%

On the Semi-Blind Mutually Referenced Equalizers for MIMO Systems

Son,

Abed-Meraim,

Duy

et al. 2023

2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)

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“…It has good performance in noise and fits several applications: not only blind source separation, but direction finding [21], [9] and frequency estimation [11] as well. In communication scenarios, it provides an excellent starting point for more optimal nonlinear receivers, such as ILSE [15], and it can be extended to handle convolutive channels [19]. Although it has been derived as a deterministic method, it is closely related to JADE [5] and other fourth-order statistics-based source separation techniques.…”

Section: Introductionmentioning

confidence: 99%

Statistical performance analysis of the algebraic constant modulus algorithm

Veen

2002

IEEE Trans. Signal Process.

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Abstract-This paper presents a large sample analysis of the covariance of the beamformers computed by the analytical constant modulus algorithm (ACMA) method for blindly separating constant modulus sources. This can be used to predict the signal-to-interference plus noise ratio (SINR) performance of these beamformers, as well as their deviation from the (nonblind) Wiener receivers to which they asymptotically converge. The analysis is based on viewing ACMA as a subspace fitting optimization, where the subspace is spanned by the eigenvectors of a fourth-order covariance matrix. The theoretical performance is illustrated by numerical simulations and shows a good match.

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“…The approach we present takes advantage of information about the pilot data from the beginning, and uses it simultaneously with the CM assumption to find the beamformer of the desired signal directly. The new algorithm is similar in spirit to previous extensions of ACM that exploit structure in the data due to channel memory [6] or space-time block coding [7].…”

Section: Introductionmentioning

confidence: 88%

A semi-blind algebraic constant modulus algorithm

Swindlehurst

2004 IEEE International Conference on Acoustics, Speech, and Signal Processing

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A modification to the Algebraic Constant Modulus (ACM) algorithm is proposed that exploits the presence of known pilot symbols within the transmitted data. The pilot symbols are used to place soft constraints on the subspace in which the ACM solution should lie, and relax some of the identifiability conditions required by ACM. The primary advantage of the proposed method is that sources transmitting linearly independent pilot data can be separated without resorting to a joint diagonalization procedure, and hence without computing the beamformers of signals that are not of interest.

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Combining blind equalization with constant modulus properties

Abstract: This paper presents an approach to multi-user

Cited by 4 publications

References 11 publications

On the Semi-Blind Mutually Referenced Equalizers for MIMO Systems

On the Semi-Blind Mutually Referenced Equalizers for MIMO Systems

Statistical performance analysis of the algebraic constant modulus algorithm

A semi-blind algebraic constant modulus algorithm

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