| Paper: | MLSP-P4.1 | ||
| Session: | Machine Learning Applications | ||
| Time: | Thursday, May 20, 09:30 - 11:30 | ||
| Presentation: | Poster | ||
| Topic: | Machine Learning for Signal Processing: Communications Applications | ||
| Title: | DEMODULATION FOR WIRELESS ATM NETWORK USING MODIFIED SOM NETWORK | ||
| Authors: | Jiang Li; University of Texas, Arlington | ||
| Qilian Liang; University of Texas, Arlington | |||
| Michael T. Manry; University of Texas, Arlington | |||
| Abstract: | We study the demodulation problem in time division multiple access (TDMA) wireless asynchronous transfer mode (ATM) networks, where Rician flat fading channels are considered. A linear interpolation with decision feedback combined with a modified version of the self-organizing-map (LIDF-SOM) demodulator is proposed for such a system. We obtain the training sequence by exploiting medium access control (MAC) and data link control (DLC) protocols such that a semi-blind adaptive demodulator is implemented. Simulation results show that LIDF-SOM obtains 0.4-1.0 dB gain over Rician fading channels as compared to LIDF alone. | ||
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