Iteratively Reweighted two-Stage LASSO for Block-Sparse Signal Recovery Under Finite-Alphabet Constraints

Malek Messai 1, 2 Abdeldjalil Aissa El Bey 2, 1 Karine Amis Cavalec 2, 1 Frédéric Guilloud 2, 1
2 Lab-STICC_IMTA_CACS_COM
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance
Abstract : In this paper, we derive an efficient iterative algorithm for the recovery of block-sparse signals given the finite data alphabet and the non-zero block probability. The non-zero block number is supposed to be far smaller than the total block number (block-sparse). The key principle is the separation of the unknown signal vector into an unknown support vector s and an unknown data symbol vector a. Both number (‖s‖0) and positions (s ∈ {0, 1}) of non-zero blocks are unknown. The proposed algorithms use an iterative two-stage LASSO procedure consisting in optimizing the recovery problem alternatively with respect to a and with respect to s. The first algorithm resorts on ℓ1-norm of the support vector and the second one applies reweighted ℓ1-norm, which further improves the recovery performance. Performance of proposed algorithms is illustrated in the context of sporadic multiuser communications. Simulations show that the reweighted-ℓ1 algorithm performs close to its lower bound (perfect knowledge of the support vector).
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Article dans une revue
Signal Processing, Elsevier, 2019, 157, pp.73-77. 〈10.1016/j.sigpro.2018.11.007〉
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https://hal.archives-ouvertes.fr/hal-01933349
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Soumis le : vendredi 23 novembre 2018 - 16:31:48
Dernière modification le : mercredi 6 mars 2019 - 15:10:48

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Malek Messai, Abdeldjalil Aissa El Bey, Karine Amis Cavalec, Frédéric Guilloud. Iteratively Reweighted two-Stage LASSO for Block-Sparse Signal Recovery Under Finite-Alphabet Constraints. Signal Processing, Elsevier, 2019, 157, pp.73-77. 〈10.1016/j.sigpro.2018.11.007〉. 〈hal-01933349〉

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