author = {D. Boss and K.-D. Kammeyer},
  year = {1997},
  month = {May},
  title = {Blind GSM Channel Estimation},
  volume = {2},
  pages = {1044-1048},
  URL = {http://ieeexplore.ieee.org/xpl/RecentCon.jsp?punumber=4664&conhome=1000784},
  address={Phoenix, USA},
  abstract={The bandwidth efficiency of many comm. systems could be improved if the transmission channel was estimated blindly, i.e. without resort to training sequences.  As an example, we investigate in this paper the applicability of two algorithms for the blind identification of mixed-phase linear time-invariant FIR systems to the estimation of mobile radio channels on GSM conditions.  Both approaches exploit Higher Order Statistics (HOS) of the received signal sampled at symbol rate. Although this class of algorithms is said to require an excessive number of samples to achieve acceptable performance levels, we demonstrate that it is possible with the EigenVector approach to blind Identification (EVI, view ref.) to blindly estimate realistic COST-207 channels from one GSM burst (142 samples). At a signal-to-noise ratio of 7dB, all sample channels are identified within a normalized mean square error bound of 5 per cent.},
  booktitle={IEEE 47th Vehicular Technology Conference (VTC 97)}