Cochannel signal recovery using the MUSIC algorithm and the constant modulus array

Mathur, Abhishek; Keerthi, A.V.; Shynk, J.J.

doi:10.1109/97.466707

Cited by 9 publications

(6 citation statements)

References 11 publications

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“…It was previously shown in [5] that signal cancellation in the first stage modifies the direction vectors of the received signals processed in the subsequent stages. For example, the resultant antenna response matrix of the signal captured in the second stage is given by (18) where and . Thus, although the captured user is removed from the signal mixture (indicated by the zero vector above), the direction vectors of the remaining users are shifted according to the factors (where ), corresponding to a bias.…”

Section: Direction Vector Bias Sinr and Sirmentioning

confidence: 99%

“…The joint approximate diagonalization of eigen-matrices (JADE) algorithm [17] is used for the cascade multistage CM array in order to recover correlated cochannel signals in a multipath environment. A parallel implementation of the CM array was considered in [18] where an AOA estimate is used to derive the initial weight vectors of the parallel stages. A hybrid implementation of the CM array was presented in [19] where composite weights of the cascade CM array system are copied to initialize the parallel system.…”

Section: Introductionmentioning

confidence: 99%

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A Multistage Hybrid Constant Modulus Array With Constrained Adaptation for Correlated Sources

Venkataraman

Shynk

2007

IEEE Trans. Signal Process.

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The multistage constant modulus (CM) array was previously proposed for capturing multiple received signals in a cochannel signal environment. It consists of a cascade of individual CM array stages combined with adaptive signal cancelers that remove the various signals captured across the stages. However, when the received signals are mutually correlated, the signals captured by the CM array stages are not completely canceled, and previous parallel extensions of the system do not guarantee that different signals will be captured across the stages. In this paper, we present a hybrid implementation of the multistage CM array for separating correlated signals where the canceler weights in the cascade structure provide estimates of the direction vectors of the captured signals. These estimates are then used in a parallel implementation of the linearly constrained CM (LCCM) array leading to the hybrid structure. Since the direction vectors are obtained directly from the canceler weights, the hybrid implementation does not require prior knowledge of the array response matrix and is independent of the type of antennas used in the receiver. The effect of a bias in the direction vector estimates for closely-spaced signals is analyzed, and the steady-state performance of the hybrid structure is compared to that of a conventional constrained implementation for correlated sources. Computer simulations for example cochannel scenarios are provided to illustrate various properties of the system. Mean-square-error (MSE) learning curves indicate that the proposed hybrid LCCM algorithm converges faster and has lower MSE than previous implementations.Index Terms-Adaptive array signal processing, blind signal separation, constrained adaptive beamforming, interference suppression.

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Section: Direction Vector Bias Sinr and Sirmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Multistage Hybrid Constant Modulus Array With Constrained Adaptation for Correlated Sources

Venkataraman

Shynk

2007

IEEE Trans. Signal Process.

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“…A related technique, namely the multistage CM array, based on the CM algorithm and signal cancellation can be found in [21] and [22]. Even though the basic idea of this technique and our first two algorithms are similar, the implementation is distinguishable.…”

Section: Introductionmentioning

confidence: 99%

“…That is, the multistage CM array adaptively detects the transmitted signals by using a sample-by-sample technique, whereas the proposed algorithms are based on block iterative techniques, which are suitable for rapidly changing scenarios. In addition, to detect the transmitted signal, our parallel algorithm employs the concept of signal cancellation, whereas the parallel implementation proposed in [22] uses an appropriate initialisation provided by the multiple signal classification (MUSIC) algorithm [23].…”

Section: Introductionmentioning

confidence: 99%

Blind source separation of instantaneous MIMO systems based on the least-squares Constant Modulus Algorithm

Sansrimahachai

Ward

Constantinides

2005

IEE Proc., Vis. Image Process.

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Blind symbol detection for mobile communications systems has been widely studied and can be implemented by using either adaptive or iterative techniques. However, adaptive blind algorithms require data of sufficient length to converge. Therefore, in a rapidly changing environment, they are likely unable to track the changing channels. In such a situation, one possible solution is to use iterative blind algorithms. Iterative blind source separation algorithms based on the least-squares constant modulus algorithm (LSCMA) for instantaneous multipleinput multiple-output (MIMO) systems are proposed. Since the LSCMA cannot guarantee correct separation and hence cannot be used directly for MIMO channels, two extensions are considered: cancellation techniques (successive and parallel), and using an orthogonality constraint to ensure independence among different outputs. In common with many block iterative algorithms, it is found that for small block sizes there can be a BER flare-up effect at high SNR, although this can be removed for a sufficiently large block size. Of the proposed algorithms, simulation results show that the orthogonality-based algorithm has the best performance, and is comparable to iterative least-squares with projection (ILSP) algorithm, but offers cheaper computational complexity.

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“…In particular, constant modulus algorithms (CMAs) assume that sources are phase modulated and say that every entry of S should have a unit magnitude: |S i j | 1. Following the work of Treichler et al [2], this has e.g., led to the "Constant-Modulus Array" [3,4].…”

Section: Absmentioning

confidence: 99%

Blind source separation based on combined direction finding and constant modulus properties

Veen

Ninth IEEE Signal Processing Workshop on Statistical Signal and Array Processing (Cat. No.98TH8381)

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In the blind separation of instantaneous mixtures of multiple cochannel signals using an antenna array, two types of techniques have been used: based on properties of the array manifold, or based on properties of the signals. A well-studied example of the first type is the ESPRIT algorithm, which exploits the parametric structure of the array manifold. A representative of the second type is ACMA, which gives algebraic expressions for the separation of sources based on their constant modulus property, valid for phase-modulated sources. In this paper, we show that the two properties can be combined into a single algorithm.

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Cochannel signal recovery using the MUSIC algorithm and the constant modulus array

Cited by 9 publications

References 11 publications

A Multistage Hybrid Constant Modulus Array With Constrained Adaptation for Correlated Sources

A Multistage Hybrid Constant Modulus Array With Constrained Adaptation for Correlated Sources

Blind source separation of instantaneous MIMO systems based on the least-squares Constant Modulus Algorithm

Blind source separation based on combined direction finding and constant modulus properties

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