GMSK NEURAL NETWORK BASED DEMODULATOR

In this paper, the pattern recognition characteristics of the Artificial Neural Net­ works are used to realise a real demodulator for Gaussian Minimum Shift­Keying signals, used in the GSM telecommunications. The demodulator utilises the Learning Vector Quantisation (LVQ) neural network. It offers both greater efficiency in demodulating and less sensitivity to noise. In order to solve the problem regarding input signal synchronisation, a pre­processing phase is organised. The demodulator prototype has been realised by implementing the pre­processing phase and the LVQ neural network on TMS320C30 Digital Signal Processor. The demodulator has been tested according to the European Telecommunication Standard Institute Recommendations.