The DOI matches its Crossref record.
Massive MIMO: An Introduction
Abstract
Demand for wireless throughput, both mobile and fixed, will always increase. One can anticipate that, in five or ten years, millions of augmented reality users in a large city will want to transmit and receive 3D personal high-definition video more or less continuously, say 100 megabits per second per user in each direction. Massive MIMO-also called Large-Scale Antenna Systems-is a promising candidate technology for meeting this demand. Fifty-fold or greater spectral efficiency improvements over fourth generation (4G) technology are frequently mentioned. A multiplicity of physically small, individually controlled antennas performs aggressive multiplexing/demultiplexing for all active users, utilizing directly measured channel characteristics. Unlike today's Point-to-Point MIMO, by leveraging time-division duplexing (TDD), Massive MIMO is scalable to any desired degree with respect to the number of service antennas. Adding more antennas is always beneficial for increased throughput, reduced radiated power, uniformly great service everywhere in the cell, and greater simplicity in signal processing. Massive MIMO is a brand new technology that has yet to be reduced to practice. Notwithstanding, its principles of operation are well understood, and surprisingly simple to elucidate.
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
Massive MIMO in Real Propagation Environments: Do All Antennas Contribute Equally?
Gao, X., Edfors, O., Tufvesson, F., & Larsson, E. G. (2015) · IEEE Transactions on Communications · doi:10.1109/tcomm.2015.2462350 · Cited by 273
Millimetre wave frequency band as a candidate spectrum for 5G network architecture: A survey
Al-Falahy, N., & Alani, O. Y. K. (2019) · Physical Communication · doi:10.1016/j.phycom.2018.11.003 · Cited by 138
Akram, N., Madanayake, A., Venkatakrishnan, S. B., Volakis, J. L., Psychogiou, D., Marzetta, T. L., & Rappaport, T. S. (2021) · 2021 IEEE Space Hardware and Radio Conference (SHaRC) · doi:10.1109/sharc51853.2021.9375888 · Cited by 8
Self-citation
Metadata
- Authors
- Marzetta, T. L.
- Venue
- Bell Labs Technical Journal
- Published
- 2015
- Volume
- 20
- Pages
- 11-22
- ISSN
- 1089-7089 (ISSN-L)
- 1538-7305
- OpenAlex
- W2171066806
- Cited by
- 604
- References
- 0
- FWCI
- 31.27
- 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: Massive MIMO: An Introduction. https://app.cochat.ai/papers/10.15325/bltj.2015.2407793
- The paper
- Marzetta, T. L. (2015). Massive MIMO: An Introduction. Bell Labs Technical Journal. https://doi.org/10.15325/bltj.2015.2407793
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.
