Improved ML Channel Estimation for Uplink MC-CDMA Systems in Closely Spaced Multipath Channels

In order to attain near-single user performance in uplink multicarrier code- division multiple-access (MC-CDMA) systems, multiuser detection (MUD) methods may be employed which rely on simultaneous estimation of the channel frequency responses of multiple users. Pilot symbol assisted (PSA) channel estimation is needed in fast fading channels and it can be performed either by applying maximum likelihood (ML) criterion or minimum mean-squared error (MMSE) criterion. The performance of ML estimation technique degrades significantly in the case of fractionally spaced (FS) multipath channels where dominant paths are closely spaced with respect to the time resolution of the system. In such situation, the number of effective paths (which contribute more towards signal power) becomes considerably less than the actual number of multipaths at low and moderate SNR values. We propose an improved ML estimation method which considers only effective paths during the estimation process. The proposed method performs nearly identical to the MMSE estimation method and it can also provide significant reduction in the computational complexity when a large number of users are accommodated in the system.