Bit Error Probability Analysis for Massive MIMO Wireless Communications utilizing Zero Forcing Precoding
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Abstract
This article derives bit error probability (BEP) for massive multiple-input, multiple-output (M-MIMO) wireless communication, utilizing zero-forcing precoding. Frequency-flat fading channel is focused on this research work. The author utilizes the first-order Neumann series to analyze a closed-form expression for the normalization factor of the M-MIMO system, and proves that the probability distribution function (PDF) for the effective noise approaches the Gaussian distribution. A closed-form expression for the variance is additionally analyzed, and the derived PDF is then chosen to analyze the BEP for the M-MIMO system, utilizing B/QPSK (Binary/Quadrature phase shift keying) and ð-QAM (ð-ary Quadrature amplitude modulation), with Gray-coded mapping. The analytical results are validated through Monte-Carlo simulation, and the empirical results confirmed that the derived BEP significantly matched the exact results. Focusing on a system with 512 transmit antennas and 20 users, the derived BEP for 16-QAM at ðļð/ð0 = -5 dB was 4 Ã 10-3, and the deviation between the analysis and the exact BEP was only 4.78 Ã 10-6. Thus, the proposed BEP analysis can be utilized for analyzing performance of M-MIMO system efficiently.
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References
C. -X. Wang, et. al., "On the Road to 6G: Visions, Requirements, Key Technologies, and Testbeds," IEEE Commun. Surv. Tut.,
vol. 25, no. 2, pp. 905-974, 2023.
N. Fatema, G. Hua, Y. Xiang, D. Peng and I. Natgunanathan, "Massive MIMO Linear Precoding: A Survey," IEEE Syst. J., vol.
, no. 4, pp. 3920-3931, 2018.
M. A. Albreem, A. H. A. Habbash, A. M. Abu-Hudrouss and S. S. Ikki, "Overview of Precoding Techniques for Massive MIMO,"
IEEE Access, vol. 9, pp. 60764-60801, 2021.
F. Rusek et al., "Scaling Up MIMO: Opportunities and Challenges with Very Large Arrays," IEEE Signal Process. Mag., vol. 30,
no. 1, pp. 40-60, 2013.
J. Hoydis, S. T. Brink and M. Debbah, "Massive MIMO in the UL/DL of Cellular Networks: How Many Antennas Do We Need?,"
in IEEE J. Sel. Areas in Commun., vol. 31, no. 2, pp. 160-171, 2013.
H. Falconet, L. Sanguinetti, A. Kammoun and M. Debbah, "Asymptotic Analysis of Downlink MISO Systems Over Rician Fading Channels," in Proc. IEEE Int. Conf. Acoustics Speech Signal Process., pp. 3926-3930, 2016.
R. Yao, T. Li, Y. Liu, X. Zuo and H. Liu, "Analytical Approximation of the Channel Rate for Massive MIMO System With Large But Finite Number of Antennas," IEEE Access, vol. 6, pp. 6496-6504, 2018.
C. Zhang, Y. Jing, Y. Huang and L. Yang, "Performance Analysis for Massive MIMO Downlink With Low Complexity Approximate
Zero-Forcing Precoding," IEEE Trans. Commun., vol. 66, no. 9, pp. 3848-3864, 2018.
J. K. N. Nyarko, J. Xie, R. Yao, Y. Wang and L. Wang, "Accurate Approximation of ZF Massive MIMO Channel Rate With a Finite
Antenna Over Ricean Fading Channel," IEEE Access, vol. 6, pp. 65803-65812, 2018.
Q. -U. -A. Nadeem and A. Chaaban, "Analysis of One-Bit Quantized Linear Precoding Schemes in Multi-Cell Massive MIMO Downlink," IEEE Trans. Commun., vol. 72, no. 5, pp. 2577-2594, 2024.
L. G. Ordonez, D. P. Palomar, A. Pages-Zamora and J. RodrÃguez Fonollosa, "Minimum BER Linear MIMO Transceivers With
Adaptive Number of Substreams," in IEEE Trans, Signal Process., vol. 57, no. 6, pp. 2336-2353, 2009.
L. Zhao, K. Zheng, H. Long, H. Zhao, âPerformance Analysis for Downlink Massive MIMO System With ZF Precodingâ, in Proc.
Trans. Emerging Telecom. Technol., 2013.
S. Jacobsson, G. Durisi, M. Coldrey and C. Studer, "Linear Precoding With Low-Resolution DACs for Massive MU-MIMOOFDM Downlink," in IEEE Trans. Wireless Commun., vol. 18, no. 3, pp. 1595-1609, 2019.
M. Wu, B. Yin, G. Wang, C. Dick, J. R. Cavallaro and C. Studer, "Large-Scale MIMO Detection for 3GPP LTE: Algorithms and
FPGA Implementations," IEEE J. Sel. Topics Signal Process., vol. 8, no. 5, pp. 916-929, 2014.
R. S. Kshetrimayum, Fundamental of MIMO Wireless Communications, Cambridge, UK: Cambridge university press, 2017.
D. Chumchewkul and C. C. Tsimenidis, âClosed-Form Bit Error Probability of ZF Detection for OFDM-M-MIMO Systems Using
Effective Noise PDF,â IEEE Access, vol. 10, pp. 104384-104397, 2022.
A. Papoulis and S. U. Pillai, Probability, Random Variables, and Stochastic Processes, London: McGraw-Hill, 4th ed., 2002.
J. G. Proakis, Digital Communications. New York, USA: McGrawHill, 4th ed., 2001.
The GCC team, âGCC, the GNU Compiler Collection.â [Online]. Available: https://gcc.gnu.org/. [Accessed: Feb. 24, 2026].
C. Sanderson and R. Curtin, âArmadillo: An Efficient Framework for Numerical Linear Algebra,â in Proc. Int. Conf. Computer
Autom. Eng., 2025.
Python software foundation, âWelcome to Python.org.â [Online]. Available: https://www.python.org. [Accessed: Feb. 24, 2026].