Performance Analysis of 5G Massive MIMO Networks Using Hybrid Beamforming and Geometric Channel Models
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Abstract
This paper analyzes the performance of a 5G massive MIMO network based on hybrid beamforming (HBF) on geometric channels of 3GPP TR 38.901. The evaluation is carried out through link/system-level simulations at 28 GHz (OFDM 400 MHz), BS 128 antennas, 8 UEs, HBF architecture with N_RF.∈{12,16} and a 3–4 bit phase shifter, covering both UMi street canyon and indoor office (LOS/NLOS) scenarios. Channel estimation and precoder/combiner design follow the framework of compressed/hierarchical beam training and factorization of fully digital solutions; each configuration is evaluated on ≥1000 Monte Carlo drops. Results show that HBF (N_RF=16, 4-bit) achieves ≈90–95% sum spectral efficiency (SE) over fully digital with an average gap of 3–6 bps/Hz, while N_RF=12 reduces SE by an additional ~1–2 bps/Hz but provides the highest energy efficiency (EE). Compared to fully digital, HBF improves EE by ~4–5× due to the RF-chain reduction despite a slight SE decrease. Robustness tests against angle misestimation show SE degradation slopes of approximately 0.5%/° (fully digital), ~1.2%/° (4-bit HBF), and ~1.6%/° (3-bit HBF). The differences between scenarios highlight the sensitivity of HBFs to wider angular spread indoors. Overall, HBFs with ≥4-bit and N_RF selection proportional to the number of user flows provide the best SE-EE compromise, making them feasible for 5G mmWave implementations. Future directions include beam-squint mitigation in broadband, more detailed hardware impairment modeling, and robust machine learning-based HBF design.
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[2] TL Marzetta, “Noncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas,” IEEE Trans. Wireless Commun., vol. 9, no. 11, pp. 3590–3600, Nov. 2010. DOI: 10.1109/TWC.2010.092810.091092.
[3] A. Alkhateeb, O. El Ayach, G. Leus, R.W. Heath, “Channel Estimation and Hybrid Precoding for Millimeter Wave Cellular Systems,” IEEE J. Sel. Top. Signal Process., vol. 8, no. 5, pp. 831–846, 2014. DOI: 10.1109/JSTSP.2014.2334278.
[4] OE Ayach, S. Rajagopal, S. Abu-Surra, Z. Pi, R.W. Heath, “Spatially Sparse Precoding in Millimeter Wave MIMO Systems,” IEEE Trans. Wireless Commun., vol. 13, no. 3, pp. 1499–1513, 2014. DOI: 10.1109/TWC.2014.011714.130846.
[5] F. Sohrabi, W. Yu, “Hybrid Digital and Analog Beamforming Design for Large-Scale Antenna Arrays,” IEEE J. Sel. Top. Signal Process., vol. 10, no. 3, pp. 501–513, 2016. DOI: 10.1109/JSTSP.2016.2520912.
[6] X. Gao, L. Dai, S. Han, C.-L. I, RW Heath, “Energy-Efficient Hybrid Analog and Digital Precoding for MmWave MIMO Systems With Large Antenna Arrays,” IEEE J. Sel. Areas Commun., vol. 34, no. 4, pp. 998–1009, 2016. DOI: 10.1109/JSAC.2016.2549418.
[7] MR Akdeniz, Y. Liu, MK Samimi, S. Sun, S. Rangan, TS Rappaport, E. Erkip, “Millimeter Wave Channel Modeling and Cellular Capacity Evaluation,” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1164–1179, 2014. DOI: 10.1109/JSAC.2014.2328154.
[8] JG Andrews, S. Buzzi, W. Choi, SV Hanly, A. Lozano, ACK Soong, JC Zhang, “What Will 5G Be?,” IEEE J. Sel. Areas Commun., vol. 32, no. 6, pp. 1065–1082, 2014. DOI: 10.1109/JSAC.2014.2328098.
[9] S. Deng, MK Samimi, T.S. Rappaport, “28 GHz and 73 GHz Millimeter-Wave Indoor Propagation Measurements and Path Loss Models,” Proc. IEEE ICC Workshops, 2015. DOI: 10.1109/ICCW.2015.7247348.
[10] MK Samimi, TS Rappaport, “3-D Statistical Channel Model for Millimeter-Wave Outdoor Mobile Broadband Communications,” Proc. IEEE ICC, 2015, pp. 2430–2436. DOI: 10.1109/ICC.2015.7248689.
[11] GR MacCartney, TS Rappaport, “73 GHz Millimeter Wave Propagation Measurements for Outdoor Urban Mobile and Backhaul Communications in New York City,” Proc. IEEE ICC, 2014, pp. 4862–4867. DOI: 10.1109/ICC.2014.6884090.
[12] T.S. Rappaport, S. Deng, “73 GHz Wideband Millimeter-Wave Foliage and Ground Reflection Measurements and Models,” Proc. IEEE ICC Workshops, 2015, pp. 1238–1243. DOI: 10.1109/ICCW.2015.7247347.
[13] A.F. Molisch, V.V. Ratnam, S. Han, Z. Li, S.L.H. Nguyen, L. Li, K. Haneda, “Hybrid Beamforming for Massive MIMO – A Survey,” IEEE Communications Magazine, vol. 55, no. 9, pp. 134–141, Sept. 2017. DOI: 10.1109/MCOM.2017.1600400.
[14] X. Yu, J.-C. Shen, J. Zhang, KB Letaief, “Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems,” IEEE J. Sel. Top. Signal Process., vol. 10, no. 3, pp. 485–500, 2016. DOI: 10.1109/JSTSP.2016.2523903.
[15] J.P. González-Coma, J. Rodríguez-Fernández, N. González-Prelcic, L. Castedo, R.W. Heath, “Channel Estimation and Hybrid Precoding for Frequency-Selective Multiuser mmWave MIMO Systems,” IEEE J. Sel. Top. Signal Process., 2018. DOI: 10.1109/JSTSP.2018.2819130.
[16] S. Hamid, S.M. Sait, M.A. Jan, “Hybrid Beamforming in Massive MIMO for Next-Generation Wireless Networks: A Survey,” Sensors, 2023. (An open-access review summarizing analog/digital/hybrid architectures).
[17] L. Carneiro de Souza, L.A. Magalhães, “A Study on Propagation Models for 60 GHz Signals in Indoor Environments,” Frontiers in Communications and Networks, 2022. DOI: 10.3389/frcmn.2021.757842.
[18] TS Rappaport, GR MacCartney, et al., “Wideband Millimeter-Wave Propagation Measurements and Channel Models for Future Wireless Communication System Design,” (NYU WIRELESS/IEEE—publication summary and multi-band wideband measurement link).