Improving BER Performance of Massive MIMO Scheme over Rayleigh Fading Channel
In massive multiple input multiple output (mMIMO) scheme, the system capacity can be improved without additional bandwidth or transmit power by using a huge antenna array at base station with as much separation between antenna elements as possible. Unfortunately, its performance depends on having a perfect channel state estimate between the base state and the users. In this paper, the bit error rate (BER) performance of a mMIMO scheme is improved using genetic algorithm-based optimization with simulation performed in MATLAB software environment. The genetic algorithm used selects the best signal required for effective transmission. Four different antenna configurations in the order of 2x2, 4x4, 8x8 and 16x16 were considered for the simulation. The encoding and decoding were done using an STBC coded. Also, filter bank multicarrier-offset quadrature amplitude modulation (FBMC-OQAM) scheme was used and simulation was carried out for 4-FBMC-OQAM, 16 FBMC-OQAM, and 64 FBMC-OQAM order. The BER is computed for both the optimized and un-optimized mMIMO schemes, and the performance of both schemes is compared. Simulation results show a significant improvement in the BER of the optimized mMIMO compared to the normal (coded) MIMO scheme. The overall results show that the optimized mMIMO experience a reduced BER when compared to the normal mMIMO. In both cases, the BER reduces gradually as the number of antenna increases.
Ayoola ST, Olasoji YO, Adedeji KB, Olebu CG, Busari SA, Popoola JJ. Effect of backhaul technologies on 3G network performance: A case study of Ado-Ekiti. European Journal of Electrical Engineering and Computer Science 2021, 5(3): 23-31.
Gozalvez J. 5G worldwide developments. IEEE Vehicular Technology Magazine 2017, 12: 4–11.
Matalatala M, Deruyck M, Shikhantsov S, Tanghe E, Plets D, Goudos S, Psannis, KE, Martens L, Joseph W. Multi-objective optimization of massive MIMO 5G wireless networks towards power consumption, uplink and downlink exposure. Applied Sciences 2019, 9: 1-20.
Osseiran A, Boccardi F, Braun V, Kusume K, Marsch P, Maternia M, Queseth O, et al. Scenarios for 5G mobile and wireless communications: the vision of the metis project. IEEE Communications Magazine 2014, 52(5): 26–35.
Palattella MR, Dohler M, Grieco A, Rizzo G, Torsner J, Engel T, Ladid L. Internet of things in the 5G era: Enablers, architecture, and business models. IEEE Journal on Selected Areas in Communications 2016, 34(3): 510–527.
Wang C, Haider F, Gao X, You X, Yang Y, Yuan D, Aggoune H, Haas H, Fletcher S, Hepsaydir E. Cellular architecture and key technologies for 5g wireless communication networks. IEEE Communications Magazine 2014, 52(2): 122–130.
Insider Intelligence, 2017, Global monthly mobile data traffic, by type in exabytes. Online: https://www.google.co.za/amp/s/www.businessinsider.com/mobile-data-will-skyrocket-700-by-2021-2017-2%3famp [accessed: 11/11/2021].
Gupta A, Jha RR. A survey of 5G network: Architecture and emerging technologies. IEEE Access 2015, 3: 1206–1232.
Boccardi F, Heath RW, Lozano A, Marzetta TL, Popovski P. Five disruptive technology directions for 5G. IEEE Communications Magazine 2014, 52(2): 74–80.
Chen S, Zhao J. The requirements, challenges, and technologies for 5G of terrestrial mobile telecommunication,” IEEE Communications Magazine 2014, 52(5): 36–43.
Kamga GN, Xia M, Aissa S. Spectral-efficiency analysis of massive MIMO system in centralized and distributed schemes. IEEE Transactions on Communications 2016, 64(5): 1930-1941.
Zhang J, Dai L, Sun S, Wang Z. On the spectral efficiency of massive MIMO system with low-resolution ADCs. IEEE Communication Letters 2016, 20(5): 842-845.
Dicandia FA, Genovesi S. Exploitation of triangular lattice arrays for improved spectral efficiency of massive MIMO 5G system. IEEE Access 2021, 9: 17530-17543.
Liu T, Tong J, Guo Q, Xi J, Yu J, Xiao X. Energy efficiency of massive MIMO system with low resolution ADCs and successive interference cancellation. IEEE Transactions on Wireless Communications 2019, 18: 3987-4002.
Tan W, Xie D, Xia J, Tan W, Fan L, Jin S. Spectral and energy efficiency of massive MIMO for hybrid architecture’s based on phase shifters. IEEE Access 2018, 6: 11751-11759.
Jose FK, Lolis LH, Mafra SB, Ribeiro EP. Spectral efficiency analysis in massive MIMO using FBMC-OQAM modulation. Journal of Microwaves, Optoelectronics and Electromagnetic Applications 2018, 17: 2179-1074.
Altamirano CD, Minango J, Mora HC, De Almeida C. ‘BER evaluation of linear detectors in massive MIMO systems under imperfect channel estimation effect. IEEE Access 2019, 7: 174482-174494.
Altamirano CD, Carvajal H, De Almeida C. BER of massive MIMO in time-variant channels using multiplex, superimposed and hybrid channel estimation techniques. AEU-International Journal of Electronics and Communications 2021, 131: 153594.
Zhang D, Mumtaz S, Hug KS. SISO to mmwave massive MIMO. In: S. Mumtaz, J. Rodriquez, and L. Dai eds., mmWave Massive MIMO: A Paradigm for 5G, Chapter 2, American Press, UK, 2017.
Ngo HG. Massive MIMO: Fundamentals and system design. In Linkoping University Electronic Press, Sweden, 2015.
Rusek F, Persson D, Lau BK, EG Larsson, Marzetta FL, Edfors O, Tufvesson F. Scaling up MIMO: Opportunities and challenges with very large arrays. IEEE Signal Processing Magazine 2003, 30(1): 40-60.
Marzetta TL. Non cooperative cellular wireless with unlimited number for base station antennas. IEEE Transactions on Wireless Communication 2010, 9(11): 3590-3600.
Ibrahim AN, Abdullah MF. The potential of FBMC over OFDM for the future 5G mobile communication Technology. AIP Conference Proceedings 2017, 1883: 020001.