The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Grassmannian beamforming for multiple-input multiple-output wireless systems
Abstract
Transmit beamforming and receive combining are simple methods for exploiting the significant diversity that is available in multiple-input multiple-output (MIMO) wireless systems. Unfortunately, optimal performance requires either complete channel knowledge or knowledge of the optimal beamforming vector; both are hard to realize. In this article, a quantized maximum signal-to-noise ratio (SNR) beamforming technique is proposed where the receiver only sends the label of the best beamforming vector in a predetermined codebook to the transmitter. By using the distribution of the optimal beamforming vector in independent and identically distributed Rayleigh fading matrix channels, the codebook design problem is solved and related to the problem of Grassmannian line packing. The proposed design criterion is flexible enough to allow for side constraints on the codebook vectors. Bounds on the codebook size are derived to guarantee full diversity order. Results on the density of Grassmannian line packings are derived and used to develop bounds on the codebook size given a capacity or SNR loss. Monte Carlo simulations are presented that compare the probability of error for different quantization strategies.
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
Golub, G. (2012) · doi:10.56021/9781421407944 · Cited by 34,505
(2007) · Electronics: A First Course · doi:10.4324/9780080477527-64 · Cited by 24,923
A simple transmit diversity technique for wireless communications
Alamouti, S. M. (1998) · IEEE Journal on Selected Areas in Communications · doi:10.1109/49.730453 · Cited by 12,784
Capacity of Multi‐antenna Gaussian Channels
Telatar, E. (1999) · European Transactions on Telecommunications · doi:10.1002/ett.4460100604 · Cited by 11,234
On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas
Foschini, G. J., & Gans, M. J. (1998) · Wireless Personal Communications · doi:10.1023/a:1008889222784 · Cited by 10,091
Microwave Mobile Communications
Jakes, W. C. (1994) · Institute of Electrical and Electronics Engineers eBooks · doi:10.1109/9780470545287 · Cited by 9,747
Tarokh, V., Seshadri, N., & Calderbank, A. R. (1998) · IEEE Transactions on Information Theory · doi:10.1109/18.661517 · Cited by 7,039
Digital Communication Over Fading Channels: A Unified Approach to Performance Analysis
Simon, M. K., & Alouini, M. (2002) · Wiley eBooks · doi:10.1002/0471200697 · Cited by 6,439
Golub, G. H., & Loan, C. F. V. (1996) · Johns Hopkins University Press eBooks · Cited by 6,027
Diversity and multiplexing: a fundamental tradeoff in multiple-antenna channels
Zheng, L., & Tse, D. N. C. (2003) · IEEE Transactions on Information Theory · doi:10.1109/tit.2003.810646 · Cited by 4,258
Cited by
On the optimality of multiantenna broadcast scheduling using zero-forcing beamforming
Taesa, & Goldsmith, A. (2006) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2005.862421 · Cited by 2,057
An overview of limited feedback in wireless communication systems
Love, D., Heath, R., N. Lau, V., Gesbert, D., Rao, B., & Andrews, M. (2008) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2008.081002 · Cited by 1,503
Self-citationOn beamforming with finite rate feedback in multiple-antenna systems
Kiran Mukkavilli, K., Sabharwal, A., Erkip, E., & Aazhang, B. (2003) · IEEE Transactions on Information Theory · doi:10.1109/tit.2003.817433 · Cited by 906
Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback
Caire, G., Jindal, N., Kobayashi, M., & Ravindran, N. (2010) · IEEE Transactions on Information Theory · doi:10.1109/tit.2010.2046225 · Cited by 537
Choi, J., Love, D. J., & Bidigare, P. (2014) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2014.2313020 · Cited by 444
Self-citation
Metadata
- Authors
- Love, D. J., Heath, R. W., & Strohmer, T.
- Venue
- IEEE Transactions on Information Theory
- Published
- 2003-10
- Volume
- 49
- Issue
- 10
- Pages
- 2735-2747
- ISSN
- 0018-9448 (ISSN-L)
- OpenAlex
- W2074863717
- Cited by
- 1,505
- References
- 28
- FWCI
- 56.65
- 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: Grassmannian beamforming for multiple-input multiple-output wireless systems. https://app.cochat.ai/papers/10.1109/tit.2003.817466
- The paper
- Love, D. J., Heath, R. W., & Strohmer, T. (2003). Grassmannian beamforming for multiple-input multiple-output wireless systems. IEEE Transactions on Information Theory. https://doi.org/10.1109/tit.2003.817466
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.
