The Study of Spatial-Time-Frequency Correlation Properties of 5G Channel Modeling of MIMO-OFDM System
Main Article Content
Abstract
The fifth generation (5G) mobile communication systems will have the speed more 100 times compared to the 4G and with the aim is to provide every propagation environment for every destination. Multiple-input multiple-output (MIMO) communication is the important technology researched for 5G systems. This paper studies the correlation properties of 5G channel modeling in MIMO system such as auto-correlation functions of time and frequency, as well as the spatial cross-correlation function. The scenarios UMi, RMa and indoor cells are investigated at 6 GHz frequency band in non-line of sight (NLOS) case. We calculate the spatial-temporal-frequency correlation functions of the 5G MIMO channel to estimate the system level in physical layer. From that, we conclude the minimum correlation values are depended on the distance of antenna elements in each transmitter and receiver side. We also identify the offset in time and frequency domains to identify the stability of the signal in a certain range.
Keywords
MIMO, 5G channel modeling, spatial cross-correlation, time auto-correlation, frequency auto-correlation
Article Details
References
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[14] V. Díaz and D. M. Aviles, A Path Loss Simulator for the 3GPP 5G Channel Models, 2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON), Lima, 2018, pp. 1-4.
[2] 3GPP- TR 25.996 V10.0.0, Technical Specification Group Radio Access Network Spatial channel model for MIMO simulation, (2011-03), (2011).
[3] ETSI TR 138 901 V14.0.0 (2017-05), 5G Study on channel model for frequencies from 0.5 to 100 GHz, 2017, (3GPP TR 38.901 version 14.0.0 Release 14).
[4] Cheng-Xiang Wang, Ji Bian, Jian Sun, Wensheng Zhang and Minggao Zhang, A Survey of 5G Channel Measurements and Models, IEEE Communications surveys and tutorials, 2018.
[5] Basim Mohammed Eldowek, Saied, El. Rabiae, Fathi Saie, 3D Modeling and Analysis of the Space–Time Correlation for 5G Millimeter Wave MIMO Channels, Wireless Personal Communications, November, 2018.
[6] Samimi, M. K., Sun, S., & Rappaport, T. S, MIMO channel modeling and capacity analysis for 5G millimeter-wave wireless systems, 10th European Conference on Antennas and Propagation (EuCAP) 2016, doi:10.1109/eucap.2016.7481507.
[7] Omar E. Ayach, et al., Spatially Sparse Precoding in Millimeter Wave MIMO Systems, IEEE Transactions on Wireless communications Vol. 13, No. 3, March, 2014.
[8] Yawei Yu, et al., 3D vs. 2D Channel Models: Spatial Correlation and Channel Capacity Comparison and Analysis, 2017 IEEE ICC Wireless Communications Symposium, 2017.
[9] K. Haneda et al., Indoor 5G 3GPP-like Channel Models for Office and Shopping Mall Environments, 2016 IEEE International Conference on Communications Workshops (ICCW), May, 2016.
[10] Shu Sun, et al., Investigation of Prediction Accuracy, Sensitivity, and Parameter Stability of Large-Scale Propagation Path Loss Models for 5G Wireless Communications, IEEE Transactions on Vehicular Technology, Vol 65, Issue 5, 2016.
[11] K. Haneda et al., Indoor 5G 3GPP-like channel models for office and shopping mall environments, 2016 IEEE International Conference on Communications Workshop (ICC), Kuala Lumpur, 2016, pp. 694-699.
[12] T. S. Rappaport, et al., Investigation and Comparison of 3GPP and NYUSIM Channel Models for 5G Wireless Communications, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), Toronto, 2017, pp. 1-5.
[13] M. Rummey, P. Kyösti, L. Hentilä, 3GPP channel model developments for 5G NR requirements and testing, 12th European Conference on Antennas and Propagation (EuCAP 2018), London, 2018, pp. 1-5.
[14] V. Díaz and D. M. Aviles, A Path Loss Simulator for the 3GPP 5G Channel Models, 2018 IEEE XXV International Conference on Electronics, Electrical Engineering and Computing (INTERCON), Lima, 2018, pp. 1-4.