  In this paper, we propose an information geometry approach (IGA) for signal
detection (SD) in ultra-massive multiple-input multiple-output (MIMO) systems.
We formulate the signal detection as obtaining the marginals of the a
posteriori probability distribution of the transmitted symbol vector. Then, a
maximization of the a posteriori marginals (MPM) for signal detection can be
performed. With the information geometry theory, we calculate the
approximations of the a posteriori marginals. It is formulated as an iterative
m-projection process between submanifolds with different constraints. We then
apply the central-limit-theorem (CLT) to simplify the calculation of the
m-projection since the direct calculation of the m-projection is of
exponential-complexity. With the CLT, we obtain an approximate solution of the
m-projection, which is asymptotically accurate. Simulation results demonstrate
that the proposed IGA-SD emerges as a promising and efficient method to
implement the signal detector in ultra-massive MIMO systems.
