Channel equalization and identification appear as key issues in improving wireless communications. It is known that the linearization of the GMSK modulation (used in the European standard GSM) leads to a continuous phase OQPSK which can be considered as a Minimum Shift Keying (MSK) modulation. Thus methods of equalization and identification when the channel is input by MSK modulated signals is worth to look at. Most algorithms consider MSK signals as two independent white binary PAM staggered signals; this is not the case in our approach. Here, MSK signals are seen, after sampling at baud rate, as colored complex discrete signals. Even if this view of MSK modulation is quite simple, it has never been utilized with the purpose of blind equalization. The particular statistics of such signals are studied, yielding an original closed-form analytical solution to blind equalization, both in the mono-variate case (SISO or SIMO) and in the source separation problem (MIMO). Simulations show a good behavior of the algorithms in terms of Bit Error Rate (BER) as a function of SNR, both in the case of blind equalization and source separation.
This paper is published in SPIE conference on advanced signal processing, July 22, 1998, San Diego, USA / Proceedings of SPIE - Volume 3461,26 (1998), Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, October 1998 and is made available as an electronic preprint with permission of SPIE. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
