The DOI matches its Crossref record; 201 of the 201 references it cites were found in a registry or an index.
Beamforming Technologies for Ultra-Massive MIMO in Terahertz Communications
Open accessAbstract
Terahertz (THz) communications with a frequency band 0.1-10 THz are envisioned as a promising solution to future high-speed wireless communication. Although with tens of gigahertz available bandwidth, THz signals suffer from severe free-spreading loss and molecular-absorption loss, which limit the wireless transmission distance. To compensate for the propagation loss, the ultra-massive multiple-input-multiple-output (UM-MIMO) can be applied to generate a high-gain directional beam by beamforming technologies. In this paper, a review of beamforming technologies for THz UM-MIMO systems is provided. Specifically, we first present the system model of THz UM-MIMO and identify its channel parameters and architecture types. Then, we illustrate the basic principles of beamforming via UM-MIMO and discuss the far-field and near-field assumptions in THz UM-MIMO. Moreover, an important beamforming strategy in THz band, i.e., beam training, is introduced wherein the beam training protocol and codebook design approaches are summarized. The intelligent-reflecting-surface (IRS)-assisted joint beamforming and multi-user beamforming in THz UM-MIMO systems are studied, respectively. The spatial-wideband effect and frequency-wideband effect in the THz beamforming are analyzed and the corresponding solutions are provided. Further, we present the corresponding fabrication techniques and illuminate the emerging applications benefiting from THz beamforming. Open challenges and future research directions on THz UM-MIMO systems are finally highlighted.
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
Cites
Fundamentals of Wireless Communication
Tse, D., & Viswanath, P. (2005) · doi:10.1017/cbo9780511807213 · Cited by 13,162
Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C. K., & Zhang, J. C. (2014) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2014.2328098 · Cited by 8,106
Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas
Marzetta, T. L. (2010) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2010.092810.091092 · Cited by 6,302
Cutting-edge terahertz technology
Tonouchi, M. (2007) · Nature Photonics · doi:10.1038/nphoton.2007.3 · Cited by 6,301
Rudge, A. W. (1982) · Electronics and Power · doi:10.1049/ep.1982.0113 · Cited by 5,027
Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays
Rusek, F., Persson, D., Lau, B. K., Larsson, E. G., Marzetta, T. L., & Tufvesson, F. (2013) · IEEE Signal Processing Magazine · doi:10.1109/msp.2011.2178495 · Cited by 4,654
Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming
Wu, Q., & Zhang, R. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2936025 · Cited by 4,566
Self-citationTowards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network
Wu, Q., & Zhang, R. (2020) · IEEE Communications Magazine · doi:10.1109/mcom.001.1900107 · Cited by 4,308
Self-citationCoding Metamaterials, Digital Metamaterials and Programmable Metamaterials
Cui, T. J., Qi, M. Q., Wan, X., Zhao, J., & Cheng, Q. (2014) · Light: Science & Applications · doi:10.1038/lsa.2014.99 · Cited by 3,801
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication
Huang, C., Zappone, A., Alexandropoulos, G. C., Debbah, M., & Yuen, C. (2019) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2922609 · Cited by 3,761
Metadata
- Authors
- Ning, B., Tian, Z., Mei, W., Chen, Z., Han, C., Li, S., Yuan, J., & Zhang, R.
- Venue
- IEEE Open Journal of the Communications Society
- Published
- 2023
- Volume
- 4
- Pages
- 614-658
- ISSN
- 2644-125X (ISSN-L)
- OpenAlex
- W4321021943
- Cited by
- 270
- References
- 201
- FWCI
- 19.64
- Type
- journal article
- Language
- en
- Open access
- gold
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: Beamforming Technologies for Ultra-Massive MIMO in Terahertz Communications. https://app.cochat.ai/papers/10.1109/ojcoms.2023.3245669
- The paper
- Ning, B., Tian, Z., Mei, W., Chen, Z., Han, C., Li, S., Yuan, J., & Zhang, R. (2023). Beamforming Technologies for Ultra-Massive MIMO in Terahertz Communications. IEEE Open Journal of the Communications Society. https://doi.org/10.1109/ojcoms.2023.3245669
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.
