Name
Abstract | ||
|---|---|---|
Linear minimum mean square error (LMMSE) is by definition the optimal channel estimator in the sense of mean square error criterion, but its practical application is limited by its high complexity. Furthermore, the LMMSE estimation method requires the knowledge of both the channel and the noise statistics, which are a priori unknown at the receiver. A wide range of techniques are proposed in the l... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1049/iet-spr.2016.0185 | IET Signal Processing |
Keywords | Field | DocType |
channel estimation,least mean squares methods,MIMO communication,OFDM modulation,statistical analysis | Mathematical optimization,Computer science,Waveform,A priori and a posteriori,Minimum mean square error,Algorithm,Communication channel,Mean squared error,Reduction (complexity),Statistics,Orthogonal frequency-division multiplexing,Estimator | Journal |
Volume | Issue | ISSN |
11 | 2 | 1751-9675 |
Citations | PageRank | References |
5 | 0.47 | 47 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Vincent Savaux | 1 | 46 | 8.64 |
| Yves Louët | 2 | 112 | 23.96 |