Improved synchronisation for superimposed training based channel estimation

This paper introduces a synchronisation method for super-imposed training (ST) based channel estimation, using periodic ST sequences. The method exploits the particular structure, occurring when the ST sequence period is larger than the channel length, of the vector containing the received signal´s first-order cyclostationary statistics. After synchronisation, any DC-offset can be removed and an unbiased channel estimate can be obtained. Necessary and sufficient conditions for synchronisation are provided. The problem of training sequence design for an improved synchronisation is also addressed. An expression for the variance of the channel estimate is obtained as well, assuming perfect synchronisation and using the designed training sequences. The proposed synchronisation method is computationally more efficient than existing methods, and yet its performance, in term of channel estimation MSE and BER, is not diminished as shown by simulations