The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination
Open accessAbstract
Since the seminal paper by Marzetta from 2010, Massive MIMO has changed from being a theoretical concept with an infinite number of antennas to a practical technology. The key concepts are adopted into the 5G New Radio Standard and base stations (BSs) with M = 64 fully digital transceivers have been commercially deployed in sub-6GHz bands. The fast progress was enabled by many solid research contributions of which the vast majority assume spatially uncorrelated channels and signal processing schemes developed for single-cell operation. These assumptions make the performance analysis and optimization of Massive MIMO tractable but have three major caveats: 1) practical channels are spatially correlated; 2) large performance gains can be obtained by multicell processing, without BS cooperation; 3) the interference caused by pilot contamination creates a finite capacity limit, as M → ∞. There is a thin line of papers that avoided these caveats, but the results are easily missed. Hence, this tutorial article explains the importance of considering spatial channel correlation and using signal processing schemes designed for multicell networks. We present recent results on the fundamental limits of Massive MIMO, which are not determined by pilot contamination but the ability to acquire channel statistics. These results will guide the journey towards the next level of Massive MIMO, which we call “Massive MIMO 2.0”.
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Cites
Fundamentals of Wireless Communication
Tse, D., & Viswanath, P. (2005) · doi:10.1017/cbo9780511807213 · Cited by 13,162
Energy and spectral efficiency of very large multiuser MIMO systems
Ngo, H. Q., Larsson, E. G., & Marzetta, T. L. (2013) · IEEE Transactions on Communications · doi:10.1109/tcomm.2013.020413.110848 · Cited by 3,173
A well-conditioned estimator for large-dimensional covariance matrices
Ledoit, O., & Wolf, M. (2004) · Journal of Multivariate Analysis · doi:10.1016/s0047-259x(03)00096-4 · Cited by 3,046 · cited 1×
“To partially overcome this issue, a classic approach is to regularize the matrix by computing the convex combination [59]”
BackgroundBeyond Massive MIMO: The Potential of Data Transmission With Large Intelligent Surfaces
Hu, S., Rusek, F., & Edfors, O. (2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2018.2816577 · Cited by 892
Ubiquitous cell-free massive MIMO communications
Interdonato, G., Björnson, E., Quoc Ngo, H., Frenger, P., & Larsson, E. G. (2019) · EURASIP Journal on Wireless Communications and Networking · doi:10.1186/s13638-019-1507-0 · Cited by 646
Self-citation
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
Power Scaling Laws and Near-Field Behaviors of Massive MIMO and Intelligent Reflecting Surfaces
Bjornson, E., & Sanguinetti, L. (2020) · IEEE Open Journal of the Communications Society · doi:10.1109/ojcoms.2020.3020925 · Cited by 423
Self-citationDeep Learning for mmWave Beam and Blockage Prediction Using Sub-6 GHz Channels
Alrabeiah, M., & Alkhateeb, A. (2020) · IEEE Transactions on Communications · doi:10.1109/tcomm.2020.3003670 · Cited by 346
Spatially-Stationary Model for Holographic MIMO Small-Scale Fading
Pizzo, A., Marzetta, T. L., & Sanguinetti, L. (2020) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2020.3000877 · Cited by 263
Self-citationWhat Physical Layer Security Can Do for 6G Security
Mitev, M., Chorti, A., Poor, H. V., & Fettweis, G. P. (2023) · IEEE Open Journal of Vehicular Technology · doi:10.1109/ojvt.2023.3245071 · Cited by 184
Metadata
- Authors
- Sanguinetti, L., Bjornson, E., & Hoydis, J.
- Venue
- IEEE Transactions on Communications
- Published
- 2020-01
- Volume
- 68
- Issue
- 1
- Pages
- 232-257
- ISSN
- 0090-6778 (ISSN-L)
- 1558-0857
- OpenAlex
- W2979317621
- Cited by
- 376
- References
- 5
- FWCI
- 16.04
- Type
- journal article
- Language
- en
- Open access
- green
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- Sanguinetti, L., Bjornson, E., & Hoydis, J. (2020). Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination. IEEE Transactions on Communications. https://doi.org/10.1109/tcomm.2019.2945792
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