The DOI matches its Crossref record.
Stochastic Modeling of THz Indoor Radio Channels
Abstract
Providing the basis for fast system simulations and the adequate design of upcoming THz communication systems, a novel stochastic 300 GHz indoor channel model is introduced. It combines both the modeling in time as well as in frequency domain in order to account for the significant frequency dispersion of ultra broadband THz channels. Not only amplitude, phase and temporal, but also spatial channel information is considered. That way, MIMO systems as well as novel antenna concepts can be simulated. Verified and calibrated frequency domain ray tracing simulations in an office scenario provide the data basis for the derivation of model parameters. Model channel realizations are tested against ray tracing predictions and channel measurements. A complete scenario-specific parameter set is given for the considered environment, so that the model can be implemented for further use and future THz communication links can be designed under consideration of realistic propagation conditions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Terahertz Band: The Last Piece of RF Spectrum Puzzle for Communication Systems
Elayan, H., Amin, O., Shihada, B., Shubair, R. M., & Alouini, M.-S. (2020) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2019.2953633 · Cited by 535
Beamforming Technologies for Ultra-Massive MIMO in Terahertz Communications
Ning, B., Tian, Z., Mei, W., Chen, Z., Han, C., Li, S., Yuan, J., & Zhang, R. (2023) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2023.3245669 · Cited by 270
Propagation Modeling for Wireless Communications in the Terahertz Band
Han, C., & Chen, Y. (2018) · IEEE Communications Magazine · doi:10.1109/mcom.2018.1700898 · Cited by 255
Metadata
- Authors
- Priebe, S., & Kurner, T.
- Venue
- IEEE Transactions on Wireless Communications
- Published
- 2013-09
- Volume
- 12
- Issue
- 9
- Pages
- 4445-4455
- ISSN
- 1536-1276 (ISSN-L)
- OpenAlex
- W2104770042
- Cited by
- 285
- References
- 0
- FWCI
- 5.59
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Stochastic Modeling of THz Indoor Radio Channels. https://app.cochat.ai/papers/10.1109/twc.2013.072313.121581
- The paper
- Priebe, S., & Kurner, T. (2013). Stochastic Modeling of THz Indoor Radio Channels. IEEE Transactions on Wireless Communications. https://doi.org/10.1109/twc.2013.072313.121581
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.