A subspace based blind identification and equalization algorithm

A subspace based blind channel identification algorithm is proposed here. This algorithm operates directly on the data domain and therefore avoids the problems associated with other algorithms which use the statistical information contained in the received signal directly. In the noiseless case, this algorithm uses the least number of symbols that can possibly be used to identify the channel exactly. In the noisy case, simulations have shown that almost exact identification can be obtained by using a few more symbols than the theoretical minimum. This is orders of magnitude better than the other blind algorithms. Once the channel has been identified by using this procedure, any of the existing equalization techniques can be used along with it to obtain the symbols.