MAATOUG, K. and CHAMBERS, J.A., 2008. Blind adaptive channel shortening with a generalized lag-hopping algorithm which employs squared auto-correlation minimization [GLHSAM]. IN: Proceedings of 2008 3rd International Conference on Systems and Networks Communications (ICSNC 2008), Sliema, Malta, 26-31 October, pp. 75-78.
A generalized blind lag-hopping adaptive channel shortening
(GLHSAM) algorithm based upon squared auto-correlation
minimization is proposed. This algorithm provides the ability
to select a level of complexity at each iteration between
the sum-squared autocorrelation minimization (SAM) algorithm
due to Martin and Johnson and the single lag autocorrelation
minimization (SLAM) algorithm proposed by Nawaz
and Chambers whilst guaranteeing convergence to high signal
to interference ratio (SIR). At each iteration a number of
unique lags are chosen randomly from the available range so
that on the average GLHSAM has the same cost as the SAM
algorithm. The performance of the proposed GLHSAM algorithm
is confirmed through simulation studies.