Name
Abstract | ||
|---|---|---|
We will derive a stochastic maximum likelihood method for estimating spatio-temporal channel parameters. Such estimators are needed in propagation studies where extensive channel measurements and sounding are required. These are seminal tasks in the process of developing advanced channel models. The proposed method employs angular Von Mises distribution model which is appropriate for directional data typically observed in channel measurement campaigns. The signal model is stochastic. The performance of the proposed method is compared to SAGE algorithm where the signal model is deterministic. The computational complexity of the proposed method is lower and channel parameters are estimated with higher fidelity because the underlying distribution model is well-suited for directional data. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/PIMRC.2004.1368317 | Personal, Indoor and Mobile Radio Communications, 2004. PIMRC 2004. 15th IEEE International Symposium |
Keywords | Field | DocType |
channel estimation,computational complexity,maximum likelihood estimation,stochastic processes,SAGE algorithm,angular Von Mises distribution model,channel measurement,channel sounding,computational complexity,directional data,spatio-temporal channel parameter estimation,stochastic maximum likelihood method,stochastic signal model | Mathematical optimization,Fidelity,Computer science,Channel sounding,Communication channel,Algorithm,Stochastic process,von Mises distribution,Real-time computing,Estimation theory,Estimator,Computational complexity theory | Conference |
Volume | ISBN | Citations |
3 | 0-7803-8523-3 | 9 |
PageRank | References | Authors |
1.17 | 19 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cássio B. Ribeiro | 1 | 1488 | 133.93 |
| Esa Ollila | 2 | 351 | 33.51 |
| Visa Koivunen | 3 | 1917 | 187.81 |