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

Fuente: arXiv
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Auteurs principaux: Yang, Jiyuan, Chen, Yan, Fan, Mingrui, Gao, Xiqi, Xia, Xiang-Gen, Slock, Dirk
Format: Preprint
Publié: 2024
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author Yang, Jiyuan
Chen, Yan
Fan, Mingrui
Gao, Xiqi
Xia, Xiang-Gen
Slock, Dirk
author_facet Yang, Jiyuan
Chen, Yan
Fan, Mingrui
Gao, Xiqi
Xia, Xiang-Gen
Slock, Dirk
contents In Part II of this two-part paper, we prove the convergence of the simplified information geometry approach (SIGA) proposed in Part I. For a general Bayesian inference problem, we first show that the iteration of the common second-order natural parameter (SONP) is separated from that of the common first-order natural parameter (FONP). Hence, the convergence of the common SONP can be checked independently. We show that with the initialization satisfying a specific but large range, the common SONP is convergent regardless of the value of the damping factor. For the common FONP, we establish a sufficient condition of its convergence and prove that the convergence of the common FONP relies on the spectral radius of a particular matrix related to the damping factor. We give the range of the damping factor that guarantees the convergence in the worst case. Further, we determine the range of the damping factor for massive MIMO-OFDM channel estimation by using the specific properties of the measurement matrices. Simulation results are provided to confirm the theoretical results.
format Preprint
id arxiv_https___arxiv_org_abs_2401_02037
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Simplified Information Geometry Approach for Massive MIMO-OFDM Channel Estimation -- Part II: Convergence Analysis
Yang, Jiyuan
Chen, Yan
Fan, Mingrui
Gao, Xiqi
Xia, Xiang-Gen
Slock, Dirk
Information Theory
In Part II of this two-part paper, we prove the convergence of the simplified information geometry approach (SIGA) proposed in Part I. For a general Bayesian inference problem, we first show that the iteration of the common second-order natural parameter (SONP) is separated from that of the common first-order natural parameter (FONP). Hence, the convergence of the common SONP can be checked independently. We show that with the initialization satisfying a specific but large range, the common SONP is convergent regardless of the value of the damping factor. For the common FONP, we establish a sufficient condition of its convergence and prove that the convergence of the common FONP relies on the spectral radius of a particular matrix related to the damping factor. We give the range of the damping factor that guarantees the convergence in the worst case. Further, we determine the range of the damping factor for massive MIMO-OFDM channel estimation by using the specific properties of the measurement matrices. Simulation results are provided to confirm the theoretical results.
title Simplified Information Geometry Approach for Massive MIMO-OFDM Channel Estimation -- Part II: Convergence Analysis
topic Information Theory
url https://arxiv.org/abs/2401.02037