Identification and Equalization of GSM Model Using Algorithm Based on Fourth Order Cumulants and PSK Constellations

In this paper, we apply a blind algorithm for Global System Mobile communication (GSM) equalization. In order to identify, blindly, the impulse response of GSM channel, we have used higher order cumulants (HOC) to build our algorithm able to simulate the measured data with high accuracy. The simulation results in noisy environment and a  for different signal to noise ratio (SNR) demonstrate that the proposed algorithm is able to estimate the impulse response of this channel blindly (i.e., without any information about the input), except that the PSK constellations are used to generate the input excitation of the GSM channel. In the part of equalization, we use the ISI (Inter-Symbol Interference) criteria and impulse response of global system in imaginary and real part representation to perform our algorithm. The simulation results demonstrate the effectiveness of the proposed algorithm

Adaptive Algorithms Versus Higher Order Cumulants for Identification and Equalization of MC-CDMA, Journal of Telecommunications and Information Technology, 2014, nr 3

In this paper, a comparative study between a blind algorithm, based on higher order cumulants, and adaptive algorithms, i.e. Recursive Least Squares (RLS) and Least Mean Squares (LMS) for MultiCarrier Code Division Multiple Access (MC-CDMA) systems equalization is presented. Two practical frequency-selective fading channels, called Broadband Radio Access Network (BRAN A, BRAN B) normalized for MC-CDMA systems are considered. In the part of MC-CDMA equalization, the Zero Forcing (ZF) and the Minimum Mean Square Error (MMSE) equalizer techniques were used. The simulation results in noisy environment and for different signal to noise ratio (SNR) demonstrate that the blind algorithm gives approximately the same results obtained by adaptive algorithms. However, the proposed algorithm presents the advantage to estimate the impulse response of these channels blindly except that the input excitation is non-Gaussian, with the low calculation cost, compared with the adaptive algorithms exploiting the information of input and output for the impulse response channel estimation

Journal of Telecommunications and Information Technology, 2014, nr 3

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