New processing techniques based on the constant modulus adaptive algorithm

Treichler, J.; Larimore, M.

doi:10.1109/tassp.1985.1164567

Cited by 232 publications

(78 citation statements)

References 8 publications

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“…We immediately see that has null space vectors (25) These are the desired null space vectors. The remaining submatrix in the center of (24) is hopefully nonsingular.…”

Section: Analysis Of the Noise-free Casementioning

confidence: 88%

“…Singularity occurs almost surely only with BPSK-type signals (for which ) [29], and for this case, a modified algorithm called RACMA has to be used to avoid the additional solutions [27]. The null space of contains vectors for which is a vector in the null space of , i.e., either vector in (25). Assuming that has full column rank, also has full column rank.…”

Section: Analysis Of the Noise-free Casementioning

confidence: 99%

“…First derived as LMS-type adaptive equalizers by Godard [8] and Treichler et al [24], [25], CMAs are straightforward to implement, robust, and computationally of modest complexity. Quite soon, the algorithms were also applied to blind beamforming (spatial source separation), which gave rise to the similar constant modulus array [21].…”

Section: Introductionmentioning

confidence: 99%

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Asymptotic properties of the algebraic constant modulus algorithm

Veen

2001

IEEE Trans. Signal Process.

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Abstract-The algebraic constant modulus algorithm (ACMA) is a noniterative blind source separation algorithm. It computes jointly beamforming vectors for all constant modulus sources as the solution of a joint diagonalization problem. In this paper, we analyze its asymptotic properties and show that (unlike CMA) it converges to the Wiener beamformer when the number of samples or the signal-to-noise ratio (SNR) goes to infinity. We also sketch its connection to the related JADE algorithm and derive a version of ACMA that converges to a zero-forcing beamformer. This gives improved performance in applications that use the estimated mixing matrix, such as in direction finding.Index Terms-Array signal processing, blind beamforming, constant modulus algorithm, simultaneous diagonalization.

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“…We immediately see that has null space vectors (25) These are the desired null space vectors. The remaining submatrix in the center of (24) is hopefully nonsingular.…”

Section: Analysis Of the Noise-free Casementioning

confidence: 88%

Section: Analysis Of the Noise-free Casementioning

confidence: 99%

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Asymptotic properties of the algebraic constant modulus algorithm

Veen

2001

IEEE Trans. Signal Process.

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“…[9]). The application of the CMA to blind beamforming is straightforward and was first considered in [10,11]; a combined spatio-temporal CMA was proposed in [12]. Blind beamforming based solely on the finite alphabet structure is developed in [13].…”

Section: A Blind Signal Separationmentioning

confidence: 99%

“…This blind CM beamforming problem was introduced in [10,11], and solved using the CMA [7], but in a restricted form: only the reception of a single signal-of-interest among other interfering signals was considered. It was observed that the algorithm can lock onto one of the interfering signals rather than the desired signal.…”

Section: A Blind Signal Separationmentioning

confidence: 99%

An analytical constant modulus algorithm

Veen

Paulraj

1996

IEEE Trans. Signal Process.

450

363

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Abstract-Iterative constant modulus algorithms such as Godard and CMA have been used to blindly separate a superposition of co-channel constant modulus (CM) signals impinging on an antenna array. These algorithms have certain deficiencies in the context of convergence to local minima and the retrieval of all individual CM signals that are present in the channel. In this paper, we show that the underlying constant modulus factorization problem is, in fact, a generalized eigenvalue problem, and may be solved via a simultaneous diagonalization of a set of matrices. With this new, analytical approach, it is possible to detect the number of CM signals present in the channel, and to retrieve all of them exactly, rejecting other, non-CM signals. Only a modest amount of samples are required. The algorithm is robust in the presence of noise, and is tested on measured data, collected from an experimental set-up.

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Aπ/4 crossed cascaded adaptive array for mobile satellite communications

Derbala

Al-Hussaini

1999

Int. J. Satell. Commun.

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Adaptive arrays in mobile communications based on any arbitrary performance criteria have many problems in tracking the desired signal at different interference angles relative to the desired one. To use the adaptive arrays efficiently in mobile communications, we need a system which is independent of interference angles. In this paper a system nominated as π/4 crossed cascaded adaptive array (π/4 CC) based on (for example) the well‐known constant modulus algorithm (CMA) is suggested. It is a four elements adaptive array, each two elements are controlled by the CMA and they are crossed by 45° angle in the vertical plane. The proposed system is examined by computer simulation and compared with the conventional system. It is found that the conventional two elements array is suffering from the capture problem and its performance is degraded at certain interference angles e.g. 25, 50, 55°,…. When the interference power is equal to the desired signal, the proposed system outperforms the conventional one. Therefore, the suggested system is more suitable in mobile communications which employs CM modulation techniques such as FM, QPSK, GMSK,…. In this article the analysis of the CMA and the proposed system are considered in detail. The system under consideration can be used also for all other adaptive arrays employing LMS, PI, and Applebaum, etc. Copyright © 1999 John Wiley & Sons, Ltd.

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New processing techniques based on the constant modulus adaptive algorithm

Cited by 232 publications

References 8 publications

Asymptotic properties of the algebraic constant modulus algorithm

Asymptotic properties of the algebraic constant modulus algorithm

An analytical constant modulus algorithm

Aπ/4 crossed cascaded adaptive array for mobile satellite communications

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