Super-resolution modeling of the indoor radio propagation channel

Results from parametric modeling of the indoor channel frequency response are presented. Minimum-norm and autoregressive (AR) are two super-resolution modeling techniques that are used on frequency domain data to form the theoretical sum-of-sinusoids model for the indoor channel-impulse response. Us...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 1998-05, Vol.47 (2), p.649-657, Article 649
Main Authors: Morrison, G., Fattouche, M.
Format: Article
Language:English
Subjects:
Applied sciences
Current measurement
Equipments and installations
Exact sciences and technology
Finite impulse response filter
Frequency domain analysis
Frequency measurement
Frequency response
Indoor radio communication
Matched filters
Mobile radiocommunication systems
Parametric statistics
Radiocommunications
Telecommunications
Telecommunications and information theory
Time domain analysis
Time measurement
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Summary:Results from parametric modeling of the indoor channel frequency response are presented. Minimum-norm and autoregressive (AR) are two super-resolution modeling techniques that are used on frequency domain data to form the theoretical sum-of-sinusoids model for the indoor channel-impulse response. Using these techniques, it is possible to check the validity of assuming Turin's model for the indoor channel. It is shown that the modeling techniques estimate the indoor channel-impulse response with a time-domain resolution better than that of current measurement systems. A competing model that matches the measured channel frequency response to a sampled finite-impulse response (FIR) filter (as opposed to AR and minimum-norm, which give arbitrary time delays) is presented. It is shown that FIR filter matching produces a parametric model that can be more compact and more accurate in terms of matching the frequency response of the channel than the conventional super-resolution techniques.
ISSN:0018-9545
1939-9359
DOI:10.1109/25.669102