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Cited by 3,398

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

A Statistical Model for Indoor Multipath Propagation

Saleh, A.A.M., Valenzuela, R.·1987·IEEE Journal on Selected Areas in Communications

Abstract

The results of indoor multipath propagation measurements using 10 ns, 1.5 GHz, radarlike pulses are presented for a medium-size office building. The observed channel was very slowly time varying, with the delay spread extending over a range up to about 200 ns and rms values of up to about 50 ns. The attenuation varied over a 60 dB dynamic range. A simple statistical multipath model of the indoor radio channel is also presented, which fits our measurements well, and more importantly, appears to be extendable to other buildings. With this model, the received signal rays arrive in clusters. The rays have independent uniform phases, and independent Rayleigh amplitudes with variances that decay exponentially with cluster and ray delays. The clusters, and the rays within the cluster, form Poisson arrival processes with different, but fixed, rates. The clusters are formed by the building superstructure, while the individual rays are formed by objects in the vicinities of the transmitter and the receiver.

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Crossref · 10.1109/jsac.1987.1146527

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Metadata

Authors
Saleh, A. A. M., & Valenzuela, R.
Venue
IEEE Journal on Selected Areas in Communications
Published
1987-02
Volume
5
Issue
2
Pages
128-137
ISSN
0733-8716 (ISSN-L)
OpenAlex
W2163363194
Cited by
3,398
References
3
FWCI
20.96
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Statistical Model for Indoor Multipath Propagation. https://app.cochat.ai/papers/10.1109/jsac.1987.1146527
The paper
Saleh, A. A. M., & Valenzuela, R. (1987). A Statistical Model for Indoor Multipath Propagation. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/jsac.1987.1146527

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.