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In Part II of this two-part paper, we prove the convergence of the simplifiedinformation geometry approach (SIGA) proposed in Part I. For a general Bayesianinference problem, we first show that the iteration of the common second-ordernatural parameter (SONP) is separated from that of the common first-ordernatural parameter (FONP). Hence, the convergence of the common SONP can bechecked independently. We show that with the initialization satisfying aspecific but large range, the common SONP is convergent regardless of the valueof the damping factor. For the common FONP, we establish a sufficient conditionof its convergence and prove that the convergence of the common FONP relies onthe spectral radius of a particular matrix related to the damping factor. Wegive the range of the damping factor that guarantees the convergence in theworst case. Further, we determine the range of the damping factor for massiveMIMO-OFDM channel estimation by using the specific properties of themeasurement matrices. Simulation results are provided to confirm thetheoretical results.

Simplified Information Geometry Approach for Massive MIMO-OFDM Channel Estimation -- Part II: Convergence Analysis