Achieving Near Optimal Sum Rate in Downlink Massive Multiple Antenna System

Muoghalu C. N., Mbachu C. B., Nwabueze C. A.

Abstract


In this paper, a massive multiple input multiple output (massive-MIMO) system with up to 600 base station antennas exploiting the channel state information (CSI) to improve the capacity of system while serving multiple UEs was proposed. Two precoding schemes: zero-forcing (ZF) and maximum ratio transmission (MRT) were implemented and used to test the effectiveness of the proposed system. In order to study the effectiveness of the system, its performance was analyzed in terms of achievable sum rate. MATLAB codes were developed for the simulations test conducted to study the sum rate performance of the system. Simulations were carried out by varying the number of base station antennas from 300 to 600 with respect to the number of users to determine the achievable sum rate of the system. Results showed that increasing the number of base station antennas brings about better spectral efficiency for optimal multiuser interference reduction such that highest sum rates: 317.5 Bits/s/Hz and 317.0 Bits/s/Hz, were achieved using ZF considering vector/matrix normalizations for number of base station antennas (M) equal to 600 and number of UEs (K) equal to 200 when sum rate is plotted against number of base station antennas in high transmitted power scenarios. Also, when sum rate is plotted against number of users, the system achieves highest sum rate of 433.7 Bits/s/Hz and 433.3 Bits/s/Hz for ZF considering vector/matrix normalizations at M 600, for K equal to 200 for high transmitted power scenarios. The results show that for low transmitted power, MRT outperforms ZF, while ZF gives better performance than MRT for high transmitted power. Generally, the results obtained revealedthat increasing the number of base station antennas can provide near optimal (or best possible) achievable sum rate and mitigate multiuser interference (MUI).


Keywords


Achievable sum rate, massive MIMO, maximum ratio transmission, multiuser interference, zero-forcing

Full Text:

PDF

References


Viswanath, P., and Tse, D. (2003). Sum capacity of the vector Gaussian broadcast channel and uplink-downlink duality. IEEE Transaction on Information Theory, 49(8), 1912-1921.

Weingarten, H., Steinberg, Y., and Shamai, S. (2006). The capacity of the Gaussian multiple-input multiple-output broadcast channel. IEEE Transactions on Information Theory, 52(9), 3936-3964.

Rusek, F., Persson, D., Lau, B.K., Larsson, E., Marzetta, T., Edfors, O., and Tufvesson, F. (2013). Scaling up MIMO: Opportunities and challenges with large arrays. IEEE Signal Processing Magazine, 30(1), 40-60.

Fehske, A., Fettweis, G., Malmodin, J., and Biczok, G. (2011). The global footprint of mobile communications: The ecological and economic perspective. IEEE Communications Magazine, 49(8), 55-62.

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

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

Mokhtari, Z., Sabbaghian,M., and Dinis, R. (2019). A survey on massive MIMO system in the presence of channel and hardware impairments. MDPI Journal, Sensors, 19(164), 1-21.

Nalband, A.H., Sarvagya, M., and Ahmed, M.R. (2020). Optimal hybrid precoding for millimeter massive MIMO systems. 3rd International Conference on Computing and Network Communications (CoCoNet’ 19), Procedia Computer Science, 171, 810-819.

Raisa, F., Abdullah, K., Ismail, A.F.B., Reza, A., Ramli, H. A.B.M, and Hashim, W. (2017). Hybrid MMSE precoding for millimeter-wave (mmW) multiuser massive MIMO systems. International Journal of Future Communication and Networking, 10(5), 29-38.

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

Anjos, G., Castaheira, D., Silva, A., Gameiro, A., Gomes, M., and Vilela, J. (2017). Joint design of massive MIMO precoder and security scheme for multiuserscenarios under reciprocal channel conditions. Wireless Communications and Mobile Computing, Volume 2017, Article ID 5396092, 1-10.

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

Hassan, M., Falou, A., and Langlais, C. (2018). 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.

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

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

Jindal, N., and Goldsmith, A. (2005). Dirty-paper coding versus TDMA for MIMO broadcast channels. IEEE Transactions on Information Theory, 51(5), 1783-1794.

Stankovic, V., and Haardt, M. (2006). Novel linear and non-linear multi-user MIMO downlink precoding with improved diversity and capacity. Proceedings of the 16th Meeting of the Wireless World Research Forum, Shanghai, China, 1-7.

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

Hoydis, J., Ten Brink, S., and Debbah, M. (2013). Massive MIMO in the UL/DL of cellular networks: How many antennas do we need? IEEE Journal on Selected Areas in Communication, 31(2), 160-171.

Jose, J., Ashikhmin, A., Marzetta, T.L., and Vishwanath, S. (2011). Pilot Contamination and Precoding in multi-cell TDD system. IEEE Transactions on Wireless Communications, 10(8), 2640-2651.

Choi, S. (2012). Massive MIMO: A lecture presentation. Special Topics, Yonsei University.

Madhow, U. (2008). Fundamentals of digital communication. Cambridge University Press, UK.

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

Burra, S.K., and Yendrapalli, R.P.R. (2010). User Scheduling Algorithm for MU-MIMO system with limited feedback. Master Thesis, Blekinge Institute of Technology, Sweden, 1-36.




DOI: http://dx.doi.org/10.52155/ijpsat.v28.2.3460

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Paulinus Eze

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.