In this letter, we design iterative receiver algorithms for joint frequency-domain equalization and decoding in a single carrier system assuming perfect channel state information. Based on an approximate inference framework that combines belief propagation (BP) and the mean field (MF) approximation, we propose two receiver algorithms with, respectively, parallel and sequential message-passing schedules in the MF part. A recently proposed receiver based on generalized approximate message passing (GAMP) is used as a benchmarking reference. The simulation results show that the BP-MF receiver with sequential passing of messages achieves the best BER performance at the expense of higher computational complexity compared to that of the GAMP receiver. The parallel BP-MF receiver has complexity similar to that of GAMP, but its low convergence rate yields poor performance, especially under high signal-to-noise ratio conditions.