Polynomial-complexity noncoherent symbol-by-symbol detection with application to adaptive iterative decoding of turbo-like codes

The problem of generating symbol-by-symbol soft decision metrics (SbSSDMs) in the presence of unknown channel parameters is considered. The motivation for this work lies in its application to iterative decoding of highperformance turbo-like codes, transmitted over channels that introduce unknown parameters in addition to Gaussian noise. Traditional methods for the exact evaluation of SbSSDMs involve exponential complexity in the sequence length. A class of problems is identified for which the SbSSDMs can be exactly evaluated with only polynomial complexity with respect to the sequence length. Utilizing the close connection between symbol-bysymbol and sequence detection, it is also shown that for the aforementioned class of problems, detection of an uncoded data sequence in the presence of unknown parameters can be performed with polynomial complexity. The applicability of this technique is demonstrated by considering the problem of iterative detection of low-density parity-check codes in the presence of unknown and time-varying carrier-phase offset. Finally, based on the proposed exact schemes, an ultra-fast approximate algorithm for performing joint iterative decoding and phase estimation is derived that is well suited for hardware implementation.