The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
Multiuser MIMO Achievable Rates With Downlink Training and Channel State Feedback
Open accessAbstract
In this paper, we consider a multiple-input-multiple-output (MIMO) fading broadcast channel and compute achievable ergodic rates when channel state information (CSI) is acquired at the receivers via downlink training and it is provided to the transmitter by channel state feedback. Unquantized (analog) and quantized (digital) channel state feedback schemes are analyzed and compared under various assumptions. Digital feedback is shown to be potentially superior when the feedback channel uses per channel state coefficient is larger than 1. Also, we show that by proper design of the digital feedback link, errors in the feedback have a minor effect even if simple uncoded modulation is used on the feedback channel. We discuss first the case of an unfaded additive white Gaussian noise (AWGN) feedback channel with orthogonal access and then the case of fading MIMO multiple access (MIMO-MAC). We show that by exploiting the MIMO-MAC nature of the uplink channel, a much better scaling of the feedback channel resource with the number of base station (BS) antennas can be achieved. Finally, for the case of delayed feedback, we show that in the realistic case where the fading process has (normalized) maximum Doppler frequency shift 0 ¿ F < 1/2, a fraction 1 - 2F of the optimal multiplexing gain is achievable. The general conclusion of this work is that very significant downlink throughput is achievable with simple and efficient channel state feedback, provided that the feedback link is properly designed.
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Cites
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Self-citation
Cited by
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
Federated Learning via Over-the-Air Computation
Yang, K., Jiang, T., Shi, Y., & Ding, Z. (2020) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2019.2961673 · Cited by 1,084
“The feedback problem can be addressed using unquantized analog feedback or quantized digital feedback [39].”
MethodMassive MIMO Systems With Non-Ideal Hardware: Energy Efficiency, Estimation, and Capacity Limits
Bjornson, E., Hoydis, J., Kountouris, M., & Debbah, M. (2014) · IEEE Transactions on Information Theory · doi:10.1109/tit.2014.2354403 · Cited by 960
Joudeh, H., & Clerckx, B. (2016) · IEEE Transactions on Communications · doi:10.1109/tcomm.2016.2603991 · Cited by 432
Foundations of MIMO Communication
Heath Jr, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276 · Cited by 426
Metadata
- Authors
- Caire, G., Jindal, N., Kobayashi, M., & Ravindran, N.
- Venue
- IEEE Transactions on Information Theory
- Published
- 2010-06
- Volume
- 56
- Issue
- 6
- Pages
- 2845-2866
- ISSN
- 0018-9448 (ISSN-L)
- OpenAlex
- W2116141601
- Cited by
- 537
- References
- 33
- FWCI
- 32.15
- Type
- journal article
- Language
- en
- Open access
- green
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