Name
Abstract | ||
|---|---|---|
We propose an efficient approach for the computation of cumulative distribution functions of N correlated Rayleigh or exponential random variables (RVs) for arbitrary covariance matrices, which arise in the design and analysis of many wireless systems. Compared to the approaches in the literature, it employs a fast and accurate randomized quasi-Monte Carlo method that markedly reduces the computat... |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/LWC.2018.2875999 | IEEE Wireless Communications Letters |
Keywords | Field | DocType |
Covariance matrices,Correlation,Computational complexity,Relays,Probability density function,Convergence,Wireless communication | Applied mathematics,Mathematical optimization,Random variable,Exponential function,Matrix (mathematics),Cumulative distribution function,Order of magnitude,Probability density function,Mathematics,Computation,Covariance | Journal |
Volume | Issue | ISSN |
8 | 2 | 2162-2337 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Reneeta Sara Isaac | 1 | 0 | 0.68 |
| Neelesh B. Mehta | 2 | 979 | 82.27 |