International Journal of Advanced Networking and Applications

Open Access Open Access  Restricted Access Subscription Access

Bit Error Rate Analysis of Multiuser Massive MIMO Wireless System Using Linear Precoding Techniques


Affiliations
1 Department of Computer Science, Federal University of Technology, Owerri, Nigeria., Nigeria
2 Department of Information Technology, Federal University of Technology, Owerri, Nigeria., Nigeria
 

This paper presents bit error rate (BER) analysis of multiuser (MU) massive multiple input multiple out (MIMO) wireless system using linear precoding techniques. Considering the increasing demand for wireless communication that will provide seamless performance to meet users satisfaction, various precoding schemes have been developed and with massive MIMO projected to be a promising technology for 5G and next generation network. Therefore, this study was basically designed to examine the effect of linear zero forcing (ZF) and minimum mean square error (MMSE) precoders on BER performance of MU massive MIMO system with up to 32 base station antennas (BS) and communicating with up to 5 user mobile terminals (MTs). A model that describes downlink operation of MU massive MIMO wireless communication system with spatial multiplexing employing linear ZF and MMSE precoders such that each user is equipped with single antenna MT resulting in overall access points of 5 antennas was developed in MATLAB. Computer simulations revealed that ZF outperformed MMSE. This observation was validated by similar report on massive MIMO in previous study.

Keywords

BER, Massive MIMO, Minimum mean square error, Precoding, Zero forcing.
User
Notifications
Font Size

  • P. Vardhan, M. Gupta, and A. Kumar, Massive MIMO-past, present and future: A review, Indian Journal of Science and Technology, 9(48), 2016, 1- 13.

  • D. Borges, P. Montezuma, R. Dinis, and P. Viegas, Energy efficient massive MIMO point-to-point communications with physical layer security: BPSK vs QPSK decomposition. 10th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Costa de Caparica, Portugal, 283–295, 2019.

  • T. L.Marzetta, Noncoorperative cellular wireless with unlimited numbers of base station antennas. IEEE Transactions on Wireless Communications, 9(11), 3590-3600, 2010.

  • S. A. Khwandah, J. P. Cosmas, P. I. Lazaridis, Z. Zaharis, and I. P. Chochilouros, Massive MIMO systems for 5G communications, Wireless Personal Communications, 120, 2101 – 2115, 2021.

  • A. Alshammari, Optimal capacity and energy efficiency of massive MIMO systems [Doctoral dissertation, University of Denver]. Electronic Theses and Dissertation, 2017.

  • H. Q. Ngo, E. G. Larsson, T. L. Marzetta, Energy and spectral efficiency of very large multiuser MIMO systems, IEEE Transactions on Communication, 61(4), 1436-1449, 2013.

  • E. G. Larsson, O. Edfors, F. Tufvesson, and T. L. Marzetta, Massive MIMO for next generation wireless systems, IEEE Communications Magazine, 2(52), 186 – 195, 2014.

  • N. Hassan, and X. Fernando, Massive MIMO wireless networks: An overview, Electronics, 6(63), 1 – 29, 2017.

  • A. B. M. Mohammad, Performance analysis of maximum ratio transmission and zero forcing precoding techniques for downlink massive multiple input multiple output system, Master Dissertation, University of Gezira, 2015.

  • K. M. Humadi, A. I. Sulyman, and A. Alsanie, Spatial modulation concept for massive multiuser MIMO systems, International Journal of Antennas and Propagation, Volume 2014, Article ID 563273, 1-9, 2014.

  • Y-G.Lim, C-B. Chae., and G. Caire, Performance analysis of massive MIMO for cell-boundary users. IEEE Transactions on Wireless Communication, arXiv:1309.7817v2, 1-15, 2015.

  • V-F. Crâşmariu, M-O. Arvinte, and S. Ciochină, Optimizated block-diagonalized precoding technique using givens rotations QR decomposition, 2017 25th European signal Processing Conference (EUSIPCO), 883-887, 2017.

  • M. Hassan, A. Falou, and C. Langlais, Performance assessment of linear precoding for 5G multi-user massive MIMO systems on a realistic 5G mmwave channel, MENACOMM 2018: IEEE Middle East and North Africa Communications Conference, Jounich, Lebanon, 1-5, 2018.

  • P. V. Amadori, and C. Masouros, Interference driven Antenna selection for massive multi-user MIMO, IEEE, 1-15, 2015.

  • J. Singh, and D. Kedia, Performance of ZF and CB precoding techniques for large-scale MU-MIMO system, International Journal of Recent Technology and Engineering, 8(2), 5529-5536, 2019.

  • S. A. S. Alquhaif, I. Ahmad, M. Rasheed, and A. Raza, An optimized hybrid beanforming for millimeter wave MU-massive MIMO system, CTEC, Special Issue’09, 93-108, 2019.

  • A. Vizziello, P. Savazzi, and K. R. Chowdhury, A Kalman based hybrid precoding for multi-user millimeter wave MIMO systems. IEEE Access, 4, 1- 11, 2016.

  • W. Moustafa, and R. Mugisha, Scheduler algorithms for MU-MIMO, Lund University, SE-221 00 Lund, Sweden, 1-86, 2017.

  • Y. Zhang, J. Gao, and Y. Liu, MRT precoding in downlink multi-user MIMO systems, EURASIP Journal on Wireless Communications and Networking, 2016(241), 1-7, 2016.

  • T. Parfait, Y. Kuang, and K. Jerry, Performance analysis and comparison of ZF and MRT based downlink massive MIMO systems, IEEE, 383-388, 2014.

  • W-S. Lee, J-H. Ro, Y-H. You, D. Hwang, and S H-K. Song, An enhanced precoder for multi user multipleinput multiple-output downlink systems, Journal of Applied Sciences, 10(4547), 1-16, 2020.

  • A.O.M. Al Janaby, 5G downlink throughput enhancement by beam consolidation at vacant traffic. Journal of Communications Software and Systems, 15(4), 311-316, 2019.


Abstract Views: 136

PDF Views: 0




  • Bit Error Rate Analysis of Multiuser Massive MIMO Wireless System Using Linear Precoding Techniques

Abstract Views: 136  |  PDF Views: 0

Authors

Onukwugha, Chinwe Gilean
Department of Computer Science, Federal University of Technology, Owerri, Nigeria., Nigeria
Njoku, Donatus Onyedikachi
Department of Computer Science, Federal University of Technology, Owerri, Nigeria., Nigeria
Jibiri, Janefrances Ebere
Department of Information Technology, Federal University of Technology, Owerri, Nigeria., Nigeria
Dimoji, Chigozie
Department of Computer Science, Federal University of Technology, Owerri, Nigeria., Nigeria

Abstract


This paper presents bit error rate (BER) analysis of multiuser (MU) massive multiple input multiple out (MIMO) wireless system using linear precoding techniques. Considering the increasing demand for wireless communication that will provide seamless performance to meet users satisfaction, various precoding schemes have been developed and with massive MIMO projected to be a promising technology for 5G and next generation network. Therefore, this study was basically designed to examine the effect of linear zero forcing (ZF) and minimum mean square error (MMSE) precoders on BER performance of MU massive MIMO system with up to 32 base station antennas (BS) and communicating with up to 5 user mobile terminals (MTs). A model that describes downlink operation of MU massive MIMO wireless communication system with spatial multiplexing employing linear ZF and MMSE precoders such that each user is equipped with single antenna MT resulting in overall access points of 5 antennas was developed in MATLAB. Computer simulations revealed that ZF outperformed MMSE. This observation was validated by similar report on massive MIMO in previous study.

Keywords


BER, Massive MIMO, Minimum mean square error, Precoding, Zero forcing.

References