Name
Abstract | ||
|---|---|---|
Compressed sensing (CS)has been rapidly adopted as an improved solution to estimate sparse channels for OFDM systems. Nowadays, there exist many algorithms to estimate the channel under this approach. The most popular algorithms belong to the greedy algorithms category. OMP is one of the most useful algorithms due its low computational complexity and good performance. However, the accuracy in this algorithm depends directly on the stopping condition. Currently, there exist many works which try to tackle this problem developing a stopping condition by a threshold. On the other hand, some others works assume this condition known, however in a real scenario it is not true. In this work a simple strategy is proposed permitting to detect the sparse level of the wireless channel and apply it to obtain an optimal solution reducing the MSE in the OFDM channel estimation. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/LATINCOM.2018.8613215 | 2018 IEEE 10th Latin-American Conference on Communications (LATINCOM) |
Keywords | Field | DocType |
optimal sparse channel estimation,unknown sparse level,wireless OFDM systems,compressed sensing,greedy algorithms category,low computational complexity,stopping condition,wireless channel,optimal solution,OFDM channel estimation | Wireless,Computer science,Signal-to-noise ratio,Algorithm,Communication channel,Greedy algorithm,Wireless sensor network,Compressed sensing,Orthogonal frequency-division multiplexing,Computational complexity theory | Conference |
ISSN | ISBN | Citations |
2330-989X | 978-1-5386-6755-2 | 0 |
PageRank | References | Authors |
0.34 | 1 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. Daniel Vera-Gonzalez | 1 | 0 | 0.34 |
| Alfonso Prieto-Guerrero | 2 | 0 | 4.39 |
| Mounir Ghogho | 3 | 1072 | 113.80 |
| Daniel Bonilla Licea | 4 | 17 | 4.92 |