Abstract
A novel Bayesian modulation classification scheme is proposed for a single-antenna system over frequency-selective fading channels. The method is based on Gibbs sampling as applied to a latent Dirichlet Bayesian network (BN). The use of the proposed latent Dirichlet BN provides a systematic solution to the convergence problem encountered by the conventional Gibbs sampling approach for modulation classification. The method generalizes, and is shown to improve upon, the state of the art.
| Original language | English (US) |
|---|---|
| Article number | 6822569 |
| Pages (from-to) | 1135-1139 |
| Number of pages | 5 |
| Journal | IEEE Signal Processing Letters |
| Volume | 21 |
| Issue number | 9 |
| DOIs | |
| State | Published - Sep 2014 |
All Science Journal Classification (ASJC) codes
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics
Keywords
- Bayesian network
- Gibbs sampling
- latent dirichlet
- modulation classification