  In this paper, we address the message-passing receiver design for the 3D
massive MIMO-OFDM systems. With the aid of the central limit argument and
Taylor-series approximation, a computationally efficient receiver that performs
joint channel estimation and decoding is devised by the framework of
expectation propagation. Specially, the local belief defined at the channel
transition function is expanded up to the second order with Wirtinger calculus,
to transform the messages sent by the channel transition function to a
tractable form. As a result, the channel impulse response (CIR) between each
pair of antennas is estimated by Gaussian message passing. In addition, a
variational expectation-maximization (EM)-based method is derived to learn the
channel power-delay-profile (PDP). The proposed joint algorithm is assessed in
3D massive MIMO systems with spatially correlated channels, and the empirical
results corroborate its superiority in terms of performance and complexity.
