Unconditional maximum likelihood channel estimation and equalisation
Ismail Lakkis, Des McLernon · 2002
A novel blind unconditional maximum likelihood algorithm for fractionally-spaced nonminimum phase FIR channel identification and equalisation is presented. The algorithm results from using a low signal to noise approximation to the average of the likelihood function with respect to the transmitted data sequence. The channel estimation equation is derived in a closed form, and the resulting algorithm is computationally efficient since it only requires the calculation of one eigenvector. Simulation results are presented to show the performance of the proposed algorithm.