A Comparative Study of Sparse Recovery and Compressed Sensing Algorithms with Application to AoA Estimation
Published in 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2016
This paper benchmarks sparse recovery and compressed sensing algorithms applied to angle-of-arrival estimation. The comparison covers recovery accuracy, computational complexity, and robustness across methods, providing practitioners with a reference for selecting an appropriate algorithm for a given AoA-estimation setting.
Recommended citation: A. Bazzi, D. T. M. Slock, L. Meilhac and S. Panneerselvan, "A Comparative Study of Sparse Recovery and Compressed Sensing Algorithms with Application to AoA Estimation," in 2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Edinburgh, UK, 2016, pp. 1-5. https://ieeexplore.ieee.org/document/7536780
Show BibTeX
@article{bazzi2016comparative,
title = {A Comparative Study of Sparse Recovery and Compressed Sensing Algorithms with Application to AoA Estimation},
author = {Ahmad Bazzi and Dirk T. M. Slock and Lisa Meilhac and S. Panneerselvan},
journal = {2016 IEEE 17th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},
pages = {1--5},
year = {2016},
month = {jul},
publisher = {IEEE},
doi = {10.1109/SPAWC.2016.7536780},
url = {https://doi.org/10.1109/SPAWC.2016.7536780},
}