Title :
Unconditional maximum likelihood channel estimation and equalisation
Author :
Lakkis, Ismail ; McLernon, Desomnd
Author_Institution :
Dept. of Electron. & Electr. Eng., Leeds Univ., UK
Abstract :
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.
Keywords :
FIR filters; digital communication; equalisers; maximum likelihood estimation; telecommunication channels; eigenvector; equalisation; fractionally-spaced nonminimum phase FIR channel identification; performance; transmitted data sequence; unconditional maximum likelihood channel estimation; Additive white noise; Blind equalizers; Channel estimation; Computational modeling; Digital communication; Equations; Finite impulse response filter; Intersymbol interference; Maximum likelihood estimation; Optimization methods;
Conference_Titel :
Signal Processing Advances in Wireless Communications, First IEEE Signal Processing Workshop on
Conference_Location :
Paris, France
Print_ISBN :
0-7803-3944-4
DOI :
10.1109/SPAWC.1997.630048