The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Multipair Full-Duplex Relaying With Massive Arrays and Linear Processing
Open accessAbstract
We consider a multipair decode-and-forward relay channel, where multiple sources transmit simultaneously their signals to multiple destinations with the help of a full-duplex relay station. We assume that the relay station is equipped with massive arrays, while all sources and destinations have a single antenna. The relay station uses channel estimates obtained from received pilots and zero-forcing (ZF) or maximum-ratio combining/maximum-ratio transmission (MRC/MRT) to process the signals. To significantly reduce the loop interference effect, we propose two techniques: i) using a massive receive antenna array; or ii) using a massive transmit antenna array together with very low transmit power at the relay station. We derive an exact achievable rate expression in closed-form for MRC/MRT processing and an analytical approximation of the achievable rate for ZF processing. This approximation is very tight, particularly for a large number of relay station antennas. These closed-form expressions enable us to determine the regions where the full-duplex mode outperforms the half-duplex mode, as well as to design an optimal power allocation scheme. This optimal power allocation scheme aims to maximize the energy efficiency for a given sum spectral efficiency and under peak power constraints at the relay station and sources. Numerical results verify the effectiveness of the optimal power allocation scheme. Furthermore, we show that, by doubling the number of transmit/receive antennas at the relay station, the transmit power of each source and of the relay station can be reduced by 1.5 dB if the pilot power is equal to the signal power, and by 3 dB if the pilot power is kept fixed, while maintaining a given quality of service.
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Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Fundamentals of Statistical Signal Processing: Estimation Theory
Sengijpta, S. K. (1995) · Technometrics · doi:10.1080/00401706.1995.10484391 · Cited by 11,076
Fundamentals of statistical signal processing: Estimation theory
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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-citationFundamentals Of Statistical Signal Processing
Kay, S. (2001) · International Linear Collider · Cited by 3,642
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
Self-citationHow much training is needed in multiple-antenna wireless links?
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Metadata
- Authors
- Ngo, H. Q., Suraweera, H. A., Matthaiou, M., & Larsson, E. G.
- Venue
- IEEE Journal on Selected Areas in Communications
- Published
- 2014-09
- Volume
- 32
- Issue
- 9
- Pages
- 1721-1737
- ISSN
- 0733-8716 (ISSN-L)
- OpenAlex
- W1970904871
- Cited by
- 398
- References
- 23
- FWCI
- 30.60
- Type
- journal article
- Language
- en
- Open access
- green
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