Name
Abstract | ||
|---|---|---|
This paper proposes an improved linear minimum mean square error (LMMSE) algorithm of adaptive order determination by taking advantage of the structure characteristics of time domain least square (LS) channel estimation based on general-purpose processor (GPP), which provides the approximate estimation approach of max-time delay and noise power. In addition, this algorithm achieves a practical channel estimation formula which greatly reduces the complexity of the algorithm by decomposing the autocorrelation matrix into some sub-matrixes on the foundation of correlation bandwidth. Then comparisons are made between the simulation performance of improved LMMSE algorithm with those of other estimation methods for further analysis. Finally, a hardware implementation scheme of the proposed algorithm on GPP is given. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ChinaCom.2012.6417604 | CHINACOM |
Keywords | DocType | Volume |
low complexity lmmse channel estimation,channel parameter,time domain ls channel estimation,gpp,adaptive order determination,approximation theory,lmmse,estimation theory,hardware implementation scheme,approximate estimation approach,delays,structure characteristics,general-purpose processor-based time domain least square channel estimation,least mean squares methods,computational complexity,wireless channels,time-domain analysis,matrix decomposition,submatrixes,correlation bandwidth,long term evolution,max-time delay,algorithm complexity,autocorrelation matrix decomposition,noise power,linear minimum mean square error algorithm,channel estimation | Conference | null |
Issue | ISSN | ISBN |
null | null | 978-1-4673-2697-1 |
Citations | PageRank | References |
0 | 0.34 | 1 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Shi | 1 | 0 | 0.34 |
| Tao Peng | 2 | 391 | 46.51 |
| Rongrong Qian | 3 | 49 | 13.30 |
| Ran Duan | 4 | 387 | 35.90 |
| Kuilin Chen | 5 | 23 | 5.00 |