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.

翻译：本文提出了一种基于信息几何方法（IGA）的超大规模多输入多输出（MIMO）系统中的信号检测（SD）方案。我们将信号检测问题转化为求解发射符号向量后验概率分布的边缘分布，进而可执行基于最大后验边缘（MPM）准则的信号检测。借助信息几何理论，我们计算了后验边缘的近似值，并将其建模为不同约束条件下子流形之间的迭代m-投影过程。由于直接计算m-投影具有指数复杂度，我们应用中心极限定理（CLT）简化了该计算过程。通过CLT，我们获得了m-投影的渐近精确近似解。仿真结果表明，所提出的IGA-SD方法有望成为超大规模MIMO系统中实现信号检测器的高效方案。