Recurrent Backpropagation networks have been used to build up a neural receiver for GSM signals. The simulations have been carried out considering an AWGN channel corrupted by ISI, fading and Doppler. The experimental results show that the neural receiver performs better than a classic coherent one and it improves its performances when the number of training samples is increased.
Recurrent backpropagation networks receiver for modulated signals over noisy channels / A. Canegalli, L. Favalli, A. Mecocci, R. Pizzi - In: Proceedings of 8th Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications (MELECON 96). 2Piscataway, NJ, United States : IEEE, 1996. - ISBN 0780331095. - pp. 933-936 (( Intervento presentato al 8. convegno Mediterranean Electrotechnical Conference on Industrial Applications in Power Systems, Computer Science and Telecommunications (Melecon 96) tenutosi a Bari nel 1996.
Recurrent backpropagation networks receiver for modulated signals over noisy channels
R. Pizzi
1996
Abstract
Recurrent Backpropagation networks have been used to build up a neural receiver for GSM signals. The simulations have been carried out considering an AWGN channel corrupted by ISI, fading and Doppler. The experimental results show that the neural receiver performs better than a classic coherent one and it improves its performances when the number of training samples is increased.
| File | Dimensione | Formato | |
|---|---|---|---|
|
00551362.pdf
accesso aperto
Tipologia:
Publisher's version/PDF
Dimensione
303.85 kB
Formato
Adobe PDF
|
303.85 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
