Fast Structured Total Least Squares Algorithm for Solving the Basic Deconvolution Problem

Mastronardi, Nicola; Lemmerling, Philippe; Huffel, Sabine Van

doi:10.1137/s0895479898345813

Cited by 68 publications

(65 citation statements)

References 22 publications

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“…Intuitively, it consists in finding the correction terms e and f with minimal Euclidean norm that allow (4) to be fulfilled for some r. An iterative solution to the above deconvolution problem was proposed in [8].…”

Section: Relative Calibrationmentioning

confidence: 99%

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Towards practical channel reciprocity exploitation: Relative calibration in the presence of frequency offset

Guillaud¹,

Kaltenberger

2013

2013 IEEE Wireless Communications and Networking Conference (WCNC)

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Abstract-Relative calibration has been proposed as a simple way to practically exploit the reciprocity of the wireless channel. It is based on a simple convolutional model for the relationship between the channel impulse responses in both directions, and accounts for the discrepancies between transmit and receive radiofrequency components, without the need for specific calibration hardware. However, the relative calibration methods developed so far have been shown to lack robustness with respect to frequency offset between the devices on both sides of the considered channel. In this article, we introduce a relative calibration algorithm that properly deals with the presence of frequency offset. We verify its robustness and assess its performance through simulations, and validate experimentally the proposed model on measured channels.

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Section: Relative Calibrationmentioning

confidence: 99%

“…Similarly to the original Structured TLS algorithm [8], no proof of convergence nor optimality of the above algorithm could be established. Simulations presented in the next sections however demonstrate adequate performance.…”

Section: Proposed Iterative Solutionmentioning

confidence: 99%

Towards practical channel reciprocity exploitation: Relative calibration in the presence of frequency offset

Guillaud¹,

Kaltenberger

2013

2013 IEEE Wireless Communications and Networking Conference (WCNC)

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“…Thus, from the study presented in [5], we selected a less computationally intensive multi-input multi-output (MIMO) calibration method consisting in dividing the MIMO channel into a single channel, then the calibration is finally performed for each subdividing channel, by total leastsquares (TLS) techniques [6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Reciprocity calibration techniques, implementation on the OpenAirInterface platform

Kouassi

Zayen

Ghauri³

et al. 2011

Proceedings of the 4th International Conference on Cognitive Radio and Advanced Spectrum Management

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The channel reciprocity is an advantageous hypothesis in cognitive radio (CR) technologies, however it is not practically exploitable due to miscellaneous discrepancies including the radio frequency (RF) impairments. Consequently, previous studies proposed calibration solutions to solve these RF impairments. This paper is a step ahead in the implementation of calibration algorithms through the EURE-COM's experimental OpenAirInterface (OAI) platform. It proposes to implement and evaluate a less computationally intensive multiple-input multiple-output (MIMO) calibration algorithm, according to a realistic scenario based on long term evolution-time division duplex (LTE-TDD) specification. The result from OAI simulator shows that it is feasible to restore the reciprocity after calibration in a non reciprocal channel, and provides an overview of the challenges in the channel estimation in a real time case.

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“…An overview of algorithms for STLS computation is given in Lemmerling (1999, Section 4), and numerically efficient algorithms based on the Generalized Schur Algorithm are developed in Mastronardi et al (2000), Lemmerling et al (2000) and Mastronardi (2001).…”

Section: Introductionmentioning

confidence: 99%

Consistency of the structured total least squares estimator in a multivariate errors-in-variables model

Kukush

Markovsky

Huffel

2005

Journal of Statistical Planning and Inference

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The structured total least squares estimator, defined via a constrained optimization problem, is a generalization of the total least squares estimator when the data matrix and the applied correction satisfy given structural constraints. In the paper, an affine structure with additional assumptions is considered. In particular, Toeplitz and Hankel structured, noise free and unstructured blocks are allowed simultaneously in the augmented data matrix. An equivalent optimization problem is derived that has as decision variables only the estimated parameters. The cost function of the equivalent problem is used to prove consistency of the structured total least squares estimator. The results for the general affine structured multivariate model are illustrated by examples of special models. Modification of the results for block-Hankel/Toeplitz structures is also given. As a by-product of the analysis of the cost function, an iterative algorithm for the computation of the structured total least squares estimator is proposed.

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Fast Structured Total Least Squares Algorithm for Solving the Basic Deconvolution Problem

Cited by 68 publications

References 22 publications

Towards practical channel reciprocity exploitation: Relative calibration in the presence of frequency offset

Towards practical channel reciprocity exploitation: Relative calibration in the presence of frequency offset

Reciprocity calibration techniques, implementation on the OpenAirInterface platform

Consistency of the structured total least squares estimator in a multivariate errors-in-variables model

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