Abstract
Problem statement: The bandwidth efficiency of many communication systems could be improved if the transmission channel was estimated blindly without resort to training sequences. GMSK was a spectrum-efficient modulation scheme and it was adopted as the modulation standard of GSM systems. Approach: However, because of its phase modulation, Gaussian filtering and partial response signalling properties, Results: The simulation results showed great potential of semi-blind identification algorithms, since we used no extra antenna or over-sampling the received signal. Conclusion: GMSK was not a linear modulation. Linear approximation of the GMSK signal made the blind equalization system model applicable for GSM. In the sequel, a linear approximation of GMSK signals was presented and a blind GSM and semi-blind channel identification algorithm based on the cross relation method was suggested.
Highlights
The Pan-European cellular standard of GSM uses a Time Division Multiple Access (TDMA) scheme, where each frequency band is shared by 8 users allocated with 8 time slots
We first present a new blind channel identification algorithm based on the cross relation method[1]
Because, existing blind equalization algorithm rely on linear system models, linear approximation of the GMSK signal becomes the necessary first step
Summary
The Pan-European cellular standard of GSM uses a Time Division Multiple Access (TDMA) scheme, where each frequency band is shared by 8 users allocated with 8 time slots. The 26 bit training sequence can be used by receivers to identify the unknown linear channel impulse response that includes transmitter filter, physical channel and receiver filter. This training sequence represents a sizable overhead that reduces the overall system efficiency. Because, existing blind equalization algorithm rely on linear system models, linear approximation of the GMSK signal becomes the necessary first step. Among the 16 different linear pulses, only two pulses are significant while the others are most zero Retaining these two most significant pulses, the linear approximate model for GMSK with BT = 0.3 is: QAM signals with pulse shapes h0(t) and h1(t).
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