Maximum Likelihood Calibration of Stochastic Multipath Radio Channel Models

被引：2

作者：

Hirsch, Christian ^{[1
]}

Bharti, Ayush ^{[2
]}

Pedersen, Troels ^{[2
]}

Waagepetersen, Rasmus ^{[3
]}

机构：

[1] Univ Groningen, Bernoulli Inst, NL-9712 CP Groningen, Netherlands

[2] Aalborg Univ, Dept Elect Syst, DK-9220 Aalborg, Denmark

[3] Aalborg Univ, Dept Math Sci, DK-9220 Aalborg, Denmark

来源：

IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION | 2021年 / 69卷 / 07期

关键词：

Delays; Stochastic processes; Calibration; Maximum likelihood estimation; Data models; Adaptation models; Power measurement; Maximum likelihood estimation (MLE); Monte Carlo methods; multipath channels; point processes; radio propagation; shot noise; ENVIRONMENTS;

D O I：

10.1109/TAP.2020.3044379

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

We propose Monte Carlo maximum likelihood estimation as a novel approach in the context of calibration and selection of stochastic channel models. First, considering a Turin channel model with inhomogeneous arrival rate as a prototypical example, we explain how the general statistical methodology is adapted and refined for the specific requirements and challenges of stochastic multipath channel models. Then, we illustrate the advantages and pitfalls of the method based on simulated data. Finally, we apply our calibration method to wideband signal data from indoor channels.

引用

页码：4058 / 4069

页数：12

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