The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?
Open accessAbstract
Massive MIMO can greatly increase both spectral and transmit-energy efficiency. This is achieved by allowing the number of antennas and RF chains to grow very large. However, the challenges include high system complexity and hardware energy consumption. Here we investigate the possibilities to reduce the required number of RF chains, by performing antenna selection. While this approach is not a very effective strategy for theoretical independent Rayleigh fading channels, a substantial reduction in the number of RF chains can be achieved for real massive MIMO channels, without significant performance loss. We evaluate antenna selection performance on measured channels at 2.6 GHz, using a linear and a cylindrical array, both having 128 elements. Sum-rate maximization is used as the criterion for antenna selection. A selection scheme based on convex optimization is nearly optimal and used as a benchmark. The achieved sum-rate is compared with that of a very simple scheme that selects the antennas with the highest received power. The power-based scheme gives performance close to the convex optimization scheme, for the measured channels. This observation indicates a potential for significant reductions of massive MIMO implementation complexity, by reducing the number of RF chains and performing antenna selection using simple algorithms.
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
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Elements of Information Theory
Cover, T. M., & Thomas, J. A. (2001) · Wiley eBooks · doi:10.1002/0471200611 · Cited by 36,808
Goldsmith, A. (2005) · Cambridge University Press eBooks · doi:10.1017/cbo9780511841224 · Cited by 10,658
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
Massive MIMO for next generation wireless systems
Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736761 · Cited by 6,779
Self-citationNoncooperative 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
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
Self-citationScaling up MIMO: Opportunities and challenges with very large arrays
Rusek, F., Persson, D., Lau, B. K., Larsson, E. G., Marzetta, T. L., Edfors, O., Tufvesson, F., Print, P., Rusek, F., Persson, D., et al. (2013) · Cited by 4,089
Self-citationWriting on dirty paper (Corresp.)
Costa, M. (1983) · IEEE Transactions on Information Theory · doi:10.1109/tit.1983.1056659 · Cited by 3,735
Five disruptive technology directions for 5G
Boccardi, F., Heath, R. W., Lozano, A., Marzetta, T. L., & Popovski, P. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736746 · Cited by 3,709
Cited by
Massive MIMO Has Unlimited Capacity
Bjornson, E., Hoydis, J., & Sanguinetti, L. (2018) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2017.2768423 · Cited by 474
Metadata
- Authors
- Gao, X., Edfors, O., Tufvesson, F., & Larsson, E. G.
- Venue
- IEEE Transactions on Communications
- Published
- 2015-11
- Volume
- 63
- Issue
- 11
- Pages
- 3917-3928
- ISSN
- 0090-6778 (ISSN-L)
- OpenAlex
- W1855653084
- Cited by
- 273
- References
- 43
- FWCI
- 15.40
- 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: Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally? https://app.cochat.ai/papers/10.1109/tcomm.2015.2462350
- The paper
- Gao, X., Edfors, O., Tufvesson, F., & Larsson, E. G. (2015). Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally? IEEE Transactions on Communications. https://doi.org/10.1109/tcomm.2015.2462350
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.