  With a unified belief propagation (BP) and mean field (MF) framework, we
propose an iterative message passing receiver, which performs joint channel
state and noise precision (the reciprocal of noise variance) estimation and
decoding for OFDM systems. The recently developed generalized approximate
message passing (GAMP) is incorporated to the BP-MF framework, where MF is used
to handle observation factor nodes with unknown noise precision and GAMP is
used for channel estimation in the time-frequency domain. Compared to
state-of-the-art algorithms in the literature, the proposed algorithm either
delivers similar performance with much lower complexity, or delivers much
better performance with similar complexity. In addition, the proposed algorithm
exhibits fastest convergence.
