Blind sequence estimation for short burst communications over time varying wireless channels

We propose a blind sequence estimator (BSE) that is well suited for short burst communication formats used in many wireless TDMA systems. It is based on per survivor processing (PSP) maximum likelihood sequence estimation (MLSE). However, the initial channel estimates needed for conventional MLSE, are obtained blindly from the on-set of a burst. This provides PSP with near-convergence initial channel estimates without the help of training sequences. Thus, this approach is effective for short burst TDMA wireless communication, since it eliminates the overhead associated with training which is significant in short burst formats. For fast time-varying frequency selective wireless channels, the proposed BSE performs similarly compared to conventional PSP MLSE with training sequences. This is mainly because the need for channel tracking limits the usefulness of training sequences.