Abstract
In this paper we propose to combine Turbo equalization and source-channel coding for the transmission of correlated sources over sensor networks. Concretely, we study an asymmetrical scheme where two correlated sources, S 1 and S2, have to be transmitted to a central node. Source S1 is compressed and transmitted over a Gaussian ISI channel, whereas the other source S2 is assumed to be available as side information at the receiver. The correlation between sources has memory and is modelled by a Hidden Markov Model (HMM). For Maximum a Posteriori (MAP) and Minimum Mean Squared Error (MMSE) equalization techniques, we propose a joint equalization and decoding scheme that achieves reliable communication of source S1 at signal to noise ratios close to the theoretical bounds set by the combination of the Slepian-Wolf and Shannon theorems.
| Original language | English |
|---|---|
| Pages (from-to) | 625-629 |
| Number of pages | 5 |
| Journal | IEEE Vehicular Technology Conference |
| Volume | 61 |
| Issue number | 1 |
| Publication status | Published - 2005 |
| Externally published | Yes |
| Event | 2005 IEEE 61st Vehicular Technology Conference -VTC 2005 - Spring Stockholm: Paving the Path for a Wireless Future - Stockholm, Sweden Duration: 30 May 2005 → 1 Jun 2005 |