Maximum likelihood calibration of stochastic multipath radio channel models

Christian Pascal Hirsch, Ayush Bharti, Troels Pedersen, Rasmus Waagepetersen

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

34 Downloads (Pure)

Abstrakt

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.

OriginalsprogEngelsk
Artikelnummer9298915
TidsskriftI E E E Transactions on Antennas and Propagation
Vol/bind69
Udgave nummer7
Sider (fra-til)4058-4069
Antal sider12
ISSN0018-926X
DOI
StatusUdgivet - 2021

Fingeraftryk

Dyk ned i forskningsemnerne om 'Maximum likelihood calibration of stochastic multipath radio channel models'. Sammen danner de et unikt fingeraftryk.

Citationsformater