Name
Abstract | ||
|---|---|---|
To cope with the limitations of traditional direct-sequence spread spectrum system application, MBOK signals have been considered owing to their high gain, fast rate, and high frequency band transmission capability. However, to address the problems of large search range, slow speed, and large complexity when receiving and searching for MBOK signals, the sparse compression search (SCS) algorithm is proposed. The idea of the SCS algorithm is to compress the frequency dimension in order to improve the frequency compensation efficiency, and to then establish the sparse processing from the code dimension and the frequency dimension, thus improving the search speed. Next, the code and frequency values are calculated by channel mapping matching. The test and analysis results show that the SCS algorithm can quickly estimate the code and frequency values, and the detection probability and the computation speed are much better than other algorithms. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1007/s11760-019-01422-7 | Signal, Image and Video Processing |
Keywords | Field | DocType |
Spread spectrum communications, MBOK, Search, Sparse compression | High-gain antenna,Pattern recognition,Frequency band,Communication channel,Algorithm,Artificial intelligence,Data compression,Frequency compensation,Mathematics,Spread spectrum,Computation,Fold (higher-order function) | Journal |
Volume | Issue | ISSN |
13 | 5 | 1863-1711 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fang Liu | 1 | 0 | 0.34 |
| Yong-Xin Feng | 2 | 6 | 8.27 |