Widely-linear beamforming

McWhorter, T.; Schreier, Peter J.

doi:10.1109/acssc.2003.1292015

Cited by 14 publications

(2 citation statements)

References 4 publications

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“…More precisely, when the SOI and observations are zeromean, jointly Gaussian but non-circular, the optimal beamformer becomes WL [6], which corresponds to a particular non-linear structure weighting linearly and independently the observations and their complex conjugate. For this reason, a WL MVDR beamformer (called WL MVDR 1 ), exploiting the potential SO non-circularity of the interference only, has been introduced recently in [9] for spectrum monitoring of radiocommunications and its implementation has been discussed in [10]. To take into account the potential SO non-circularity of both the SOI and the interference, a second WL MVDR beamformer (called WL MVDR 2 ) has been further introduced in [11], [12].…”

Section: Introductionmentioning

confidence: 99%

Third-Order Volterra MVDR Beamforming for Non-Gaussian and Potentially Non-Circular Interference Cancellation

Chevalier

Delmas

Sadok

2018

IEEE Trans. Signal Process.

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Linear beamformers are optimal, in a mean square (MS) sense, when the signal of interest (SOI) and observations are jointly Gaussian and circular. Otherwise, linear beamformers become sub-optimal. When the SOI and observations are zero-mean, jointly Gaussian and non-circular, optimal beamformers become widely linear (WL). They become non-linear with a structure depending on the unknown joint probability distribution of the SOI and observations when the latter are jointly non-Gaussian, assumption which is very common in radiocommunications. In this context, the paper aims at introducing, for small-scale systems, third-order Volterra minimum variance distortionless response (MVDR) beamformers, for the reception of a SOI, whose waveform is unknown but whose steering vector is known, corrupted by non-Gaussian and potentially non-circular interference, omnipresent in practical situations. Properties, performance, complexity and adaptive implementation of these beamformers in the presence of non-Gaussian and potentially non-circular interference are analyzed in this paper. These new beamformers are shown to always improve, in the steady state, the performance of Capon beamformer for non-gaussian/circular interference, whereas some of them improve the performance of the WL MVDR beamformer for non-Gaussian/non-circular interference. These new beamformers open new perspectives for spectrum monitoring of non-Gaussian signals and for radiocommunication networks using such signals.

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Section: Introductionmentioning

confidence: 99%

Third-Order Volterra MVDR Beamforming for Non-Gaussian and Potentially Non-Circular Interference Cancellation

Chevalier

Delmas

Sadok

2018

IEEE Trans. Signal Process.

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“…1) Array Processing: The merits of impropriety adaptation in array processing algorithms are widely studied in [99], [335]- [338]. For example, coherent processing (incorporating complementary covariance) for detection and estimation enjoys a 3dB gain over non-coherent processing [32].…”

Section: B Signal Processingmentioning

confidence: 99%

A Journey From Improper Gaussian Signaling to Asymmetric Signaling

Javed

Amin

Shihada

et al. 2020

IEEE Commun. Surv. Tutorials

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The deviation of continuous and discrete complex random variables from the traditional proper and symmetric assumption to a generalized improper and asymmetric characterization (accounting correlation between a random entity and its complex conjugate), respectively, introduces new design freedom and various potential merits. As such, the theory of impropriety has vast applications in medicine, geology, acoustics, optics, image and pattern recognition, computer vision, and other numerous research fields with our main focus on the communication systems. The journey begins from the design of improper Gaussian signaling in the interference-limited communications and leads to a more elaborate and practically feasible asymmetric discrete modulation design. Such asymmetric shaping bridges the gap between theoretically and practically achievable limits with sophisticated transceiver and detection schemes in both coded/uncoded wireless/optical communication systems. Interestingly, introducing asymmetry and adjusting the transmission parameters according to some design criterion render optimal performance without affecting the bandwidth or power requirements of the systems. This dual-flavored article initially presents the tutorial base content covering the interplay of reality/complexity, propriety/impropriety and circularity/non-circularity and then surveys majority of the contributions in this enormous journey.

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Non-data-aided adaptive beamforming algorithm based on the Widely Linear Auxiliary Vector Filter

Song

Steinwandt

Wang

et al. 2011

2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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We propose a non-data-aided adaptive beamforming algorithm based on Widely Linear (WL) processing techniques and the Auxiliary Vector Filtering (AVF) algorithm for non-circular signals, where only the steering vector of the desired user is known. The proposed Widely Linear Auxiliary Vector Filtering (WL-AVF) algorithm recursively updates the filter weights by a sequence of auxiliary vectors that are designed according to the Widely Linearly Constrained Minimum Variance (WLCMV) criterion. It takes full advantage of the second-order statistics of the non-circular data, achieving a higher maximum signal-to-interference-plus-noise ratio (SINR) than the linear AVF. Key properties of the proposed WL-AVF are analyzed. Simulation results show that the WL-AVF beamforming algorithm performs the best among the existing adaptive algorithms.

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Widely-linear beamforming

Cited by 14 publications

References 4 publications

Third-Order Volterra MVDR Beamforming for Non-Gaussian and Potentially Non-Circular Interference Cancellation

Third-Order Volterra MVDR Beamforming for Non-Gaussian and Potentially Non-Circular Interference Cancellation

A Journey From Improper Gaussian Signaling to Asymmetric Signaling

Non-data-aided adaptive beamforming algorithm based on the Widely Linear Auxiliary Vector Filter

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