  In this paper, we propose an efficient ordered-statistics decoding (OSD)
algorithm with an adaptive Gaussian elimination (GE) reduction technique. The
proposed decoder utilizes two decoding conditions to adaptively remove GE in
OSD. The first condition determines whether GE could be skipped in the OSD
process by estimating the decoding error probability. Then, the second
condition is utilized to identify the correct decoding result during the
decoding process without GE. The proposed decoder can break the ``complexity
floor'' in OSD decoders introduced by the GE overhead. Simulation results
advise that when compared with the latest schemes in the literature, the
proposed approach can significantly reduce the decoding complexity at high SNRs
without any degradation in the error-correction capability.
