Name
Title | ||
|---|---|---|
Iteratively reweighted two-stage LASSO for block-sparse signal recovery under finite-alphabet constraints. |
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 (si ∈ {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). |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.sigpro.2018.11.007 | Signal Processing |
Keywords | Field | DocType |
Block-sparsity recovery,Iterative reweighting,ℓ1-minimization,Iterative recovery algorithms,LASSO,Finite-alphabet | Mathematical optimization,L1 minimization,Iterative method,Upper and lower bounds,Lasso (statistics),Support vector machine,Algorithm,Signal recovery,Mathematics,Alphabet | Journal |
Volume | ISSN | Citations |
157 | 0165-1684 | 1 |
PageRank | References | Authors |
0.36 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Malek Messai | 1 | 20 | 5.01 |
| Abdeldjalil Aïssa-El-Bey | 2 | 162 | 25.10 |
| Karine Amis | 3 | 75 | 17.77 |
| Frédéric Guilloud | 4 | 34 | 8.66 |