The DOI matches its Crossref record.
Hybrid Beamforming for Massive MIMO: A Survey
Open accessAbstract
Hybrid multiple-antenna transceivers, which combine large-dimensional analog pre/postprocessing with lower-dimensional digital processing, are the most promising approach for reducing the hardware cost and training overhead in massive MIMO systems. This article provides a comprehensive survey of the various incarnations of such structures that have been proposed in the literature. We provide a taxonomy in terms of the required channel state information, that is, whether the processing adapts to the instantaneous or average (second-order) channel state information; while the former provides somewhat better signal- to-noise and interference ratio, the latter has much lower overhead for CSI acquisition. We furthermore distinguish hardware structures of different complexities. Finally, we point out the special design aspects for operation at millimeter-wave frequencies.
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
Prospective Multiple Antenna Technologies for Beyond 5G
Zhang, J., Bjornson, E., Matthaiou, M., Ng, D. W. K., Yang, H., & Love, D. J. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3000826 · Cited by 877
Foundations of MIMO Communication
Heath Jr, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276 · Cited by 426
A Survey of Beam Management for mmWave and THz Communications Towards 6G
Xue, Q., Ji, C., Ma, S., Guo, J., Xu, Y., Chen, Q., & Zhang, W. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2024.3361991 · Cited by 280
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
Terahertz-Based IRS-Assisted Secure Symbiotic Radio Communication: A DRL Approach
Shahwar, M., Ahmed, M., Hussain, T., Ahmad, S., Ullah Khan, W., Sheraz, M., & Chee Chuah, T. (2025) · IEEE Access · doi:10.1109/access.2025.3539088 · Cited by 11
Metadata
- Authors
- Molisch, A. F., Ratnam, V. V., Han, S., Li, Z., Nguyen, S. L. H., Li, L., & Haneda, K.
- Venue
- IEEE Communications Magazine
- Published
- 2017
- Volume
- 55
- Issue
- 9
- Pages
- 134-141
- ISSN
- 0163-6804 (ISSN-L)
- OpenAlex
- W2962785465
- Cited by
- 1,168
- References
- 0
- FWCI
- 52.25
- Type
- journal article
- Language
- en
- Open access
- green
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: Hybrid Beamforming for Massive MIMO: A Survey. https://app.cochat.ai/papers/10.1109/mcom.2017.1600400
- The paper
- Molisch, A. F., Ratnam, V. V., Han, S., Li, Z., Nguyen, S. L. H., Li, L., & Haneda, K. (2017). Hybrid Beamforming for Massive MIMO: A Survey. IEEE Communications Magazine. https://doi.org/10.1109/mcom.2017.1600400
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.
