Linear detectors and precoding methods for massive MIMO
DOI:
https://doi.org/10.5433/1679-0375.2021v42n2p209Keywords:
Detection, Precoding, Massive MIMO, Channel estimation, Wireless communicationsAbstract
Detection in multiple-input-multiple-output (MIMO) wireless communication systems is a crucial procedure in receivers since the multiple access transmission schemes generate interference due to the simultaneous transmission along with the several antennas, unlike single-input-single-output (SISO) transmission schemes. Precoding is a technique in MIMO systems used to mitigate the effects of the channel over the received signal. Hence, it is possible to adjust continuously the transmitted information to reverse the effect of the wireless channel at the receiver side. In this work, linear sub-optimal detectors and precoders for massive MIMO (M-MIMO) systems are implemented, analyzed, and compared in terms of performance-complexity trade-off. It is also being considered numerical results in both channel scenarios: a) receiver and transmitter have perfect channel state information (CSI); b) complex channel coefficients are estimated with different levels of inaccuracy. Monte-Carlo simulations (MCS) reveal that linear zero-forcing (ZF) and minimum mean squared error (MMSE) massive MIMO detectors result in a certain robustness against multi-user interference when operating under low and medium system loading, L = K/M, thanks to the favourable propagation phenomenon arising in massive MIMO systems.Downloads
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References
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BOROUJERDI, M. N.; HAGHIGHATSHOAR, S.; CAIRE, G. Low-complexity statistically robust precoder/detector computation for massive MIMO systems. IEEE Transactions on Wireless Communications, New York, v. 17, n. 10, p. 6516–6530, 2018. DOI: 10.1109/TWC.2018.2860951.
BUSCHE, H.; VANAEV, A.; ROHLING, H. SVD-based MIMO precoding and equalization schemes for realistic channel knowledge: design criteria and performance evaluation. Wireless Pers Commun, Dordrecht, v. 48, p. 347-359, 2009. DOI: 10.1007/s11277-008-9526-x.
CHOCKALINGAM, A.; RAJAN, B. S.; Large MIMO systems. Cambridge University Press, Cambridge, p. 1-15, 2014. DOI: 10.1017/CBO9781139208437.
COSTA, B.; MUSSI, A.; ABRAO, T. MIMO detectors under correlated channels. Semina: Ciências Exatas e Tecnológicas, Londrina, v. 37, n. 1, p. 3-12, 2016. DOI: 10.5433/1679-0375.2016v37n1p3.
LIANG, N.; ZHANG, W.; SHEN, C. An uplink interference analysis for massive MIMO systems with MRC and ZF receivers. IEEE Wireless Communications and Networking Conference (WCNC), Canadá, p. 310-315, 2015. DOI: 10.1109/WCNC.2015.7127488.
MARINELLO, J. C.; ABRAO, T. BER analysis of multicellular MIMO systems with increasing number of bs antennas. ArXiv, Ithaca, p. 1-8, 2014.
MARZETTA, T. L.; LARSSON, E. G.; YANG, H.; NGO, H. Q. Fundamentals of massive MIMO. Cambridge: Cambridge University Press, 2016. DOI: 10.1017/CBO9781316799895.
MI, D.; DIANATI, M.; ZHANG, L.; MUHAIDAT, S.; TAFAZOLLI, R. Massive MIMO performance with imperfect channel reciprocity and channel estimation error. IEEE Transactions on Communications, New York, v. 65, n. 9, p. 3734–3749, 2017. DOI: 10.1109/TCOMM.2017.2676088.
YOUNAS, T.; LI, J.; ARSHAD, J.; MUNIR, H. M.; TULU, M. M.; YOUNAS, O. Performance of ZF and RZF in massive MIMO with channel aging. IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC), 3., 2017, [s. l.]. Proceedings [. . . ]. [ S. l.]: IEEE Xplore, 2017. p. 930-934. DOI: 10.1109/CompComm.2017.8322680.
WIESEL, A.; ELDAR, Y. C.; SHAMAI, S. Zero-forcing precoding and generalized inverses. IEEE Transactions on Signal Processing, New York, v. 56, n. 9, p. 4409–4418, 2008. DOI: 10.1109/TSP.2008.924638.
ZU, K. Novel efficient precoding techniques for multiuser MIMO systems. New York: University of York, 2013.
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Published
2021-12-02
How to Cite
Tonin, J. M. F., & Abrao, T. (2021). Linear detectors and precoding methods for massive MIMO. Semina: Ciências Exatas E Tecnológicas, 42(2), 209–220. https://doi.org/10.5433/1679-0375.2021v42n2p209
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