Improving Network Efficiency with Antenna and User Selections in a 5G Heterogeneous Cellular Network

Authors

  • Janmoni Borah Madanapalle Institute of Technology & Science, India https://orcid.org/0000-0002-0051-0313
  • Smriti Baruah Madanapalle Institute of Technology & Science, India https://orcid.org/0000-0003-0153-1084
  • S. Yathish Kumar Reddy Madanapalle Institute of Technology & Science, India
  • M. Sasidhar Madanapalle Institute of Technology & Science, India
  • T. Sai Kiran Madanapalle Institute of Technology & Science, India
  • Subramaniam Rajasekaran Madanapalle Institute of Technology & Science, India

DOI:

https://doi.org/10.3103/S0735272724050042

Keywords:

5G, Antenna Selection, User Selection, DUS, Sumrate, Network Efficiency

Abstract

The ever-increasing demand for 5G networks necessitates innovative solutions to optimize network efficiency. In this study process, we approached conventional Randon User Selection (RUS) and Maximum Channel Gain (MCG) based on which we came up with a new method called Distance User Selection (DUS). In DUS, the users are selected based on the distance in which the nearest user is selected first and assigned to the available antennas at the base station. This method prioritizes users closer to the serving base station for association, exploiting stronger signal strength and reducing path loss. Additionally, it employs optimized antenna selection algorithms to further improve the signal quality and resource allocation. We evaluated the proposed method through simulations and compared its performance with conventional approaches in terms of throughput, sumrate, and energy efficiency. Our results demonstrate significant improvements in network efficiency, highlighting the potential of DUS and antenna selection to enhance 5G network performance and user experience.

Author Biography

Janmoni Borah, Madanapalle Institute of Technology & Science

ECE, Assistant Professor

References

D. Tse, P. Viswanath, Fundamentals of Wireless Communication (Cambridge University Press, 2005). DOI: https://doi.org/10.1017/CBO9780511807213.

A. Damnjanovic et al., “A survey on 3GPP heterogeneous networks,” IEEE Wirel. Commun., 18, No. 3, 10 (2011). DOI: 10.1109/MWC.2011.5876496.

D. Park, “Transmit antenna selection in massive MIMO systems,” 2017 International Conference on Information and Communication Technology Convergence (ICTC) (IEEE, Jeju, 2017). DOI: https://doi.org/10.1109/ICTC.2017.8191036.

S. K. Mishra, P. Pattanayak, A. K. Panda, “Combined transmit antenna selection and user scheduling in a massive MIMO broadcast system,” 2020 Advanced Communication Technologies and Signal Processing (ACTS) (IEEE, Silchar, 2020). DOI: https://doi.org/10.1109/ACTS49415.2020.9350421.

S. S. Yilmaz, B. Ozbek, “Compressive sensing based low complexity user selection for massive MIMO systems,” 2020 IEEE 91st Vehicular Technology Conference (VTC2020-Spring) (IEEE, Antwerp, 2020). DOI: https://doi.org/10.1109/VTC2020-Spring48590.2020.9129553.

C.-M. Chen, Q. Wang, A. Gaber, A. P. Guevara, S. Pollin, “User scheduling and antenna topology in dense massive MIMO networks: An experimental study,” IEEE Trans. Wirel. Commun., v.19, n.9, p.6210 (2020). DOI: https://doi.org/10.1109/TWC.2020.3001224.

Y.-X. Zhu, D.-Y. Kim, J.-W. Lee, “Joint antenna and user scheduling in the massive MIMO system over time-varying fading channels,” IEEE Access, v.9, p.92431 (2021). DOI: https://doi.org/10.1109/ACCESS.2021.3092754.

M. Guo, M. C. Gursoy, “Energy-efficient joint antenna and user selection in single-cell massive MIMO systems,” 2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP) (IEEE, Anaheim, 2018). DOI: https://doi.org/10.1109/GlobalSIP.2018.8646642.

J. Akhtar, K. Rajawat, V. Gupta, A. K. Chaturvedi, “Joint user and antenna selection in massive-MIMO systems with QoS-constraints,” IEEE Syst. J., v.15, n.1, p.497 (2021). DOI: https://doi.org/10.1109/JSYST.2020.3014867.

M. O. K. Mendonca, P. S. R. Diniz, T. N. Ferreira, L. Lovisolo, “Antenna selection in massive MIMO based on Greedy algorithms,” IEEE Trans. Wirel. Commun., v.19, n.3, p.1868 (2020). DOI: https://doi.org/10.1109/TWC.2019.2959317.

B. Błaszczyszyn, M. Haenggi, P. Keeler, S. Mukherjee, Stochastic Geometry Analysis of Cellular Networks (Cambridge University Press, 2018). DOI: https://doi.org/10.1017/9781316677339.

H. ElSawy, A. Sultan-Salem, M.-S. Alouini, M. Z. Win, “Modeling and analysis of cellular networks using stochastic geometry: a tutorial,” IEEE Commun. Surv. Tutorials, v.19, n.1, p.167 (2017).

DOI: https://doi.org/10.1109/COMST.2016.2624939

C. Chen, R. C. Elliott, W. A. Krzymien, J. Melzer, “Modeling of cellular networks using stationary and nonstationary point processes,” IEEE Access, v.6, p.47144 (2018). DOI: https://doi.org/10.1109/ACCESS.2018.2865182.

Y. A. Zakaria, E. K. I. Hamad, A. S. Abd Elhamid, K. M. El-Khatib, “Propagation measurements and calculation of path loss exponent for outdoor cellular communication systems at 3.5 GHz,” Radioelectron. Commun. Syst., v.64, n.5, p.247 (2021). DOI: https://doi.org/10.3103/S0735272721050034.

J. G. Andrews, “Seven ways that HetNets are a cellular paradigm shift,” IEEE Commun. Mag., 51, No. 3, 136 (2013). DOI: 10.1109/MCOM.2013.6476878.

Borah, J., Baruah, S., Das, S. et al., “Analysis of Massive MIMO and Small Cells based 5G Cellular Networks: Simulative Approach,” Radioelectron. Commun. Syst. 65, 284–292 (2022). https://doi.org/10.3103/S0735272722060024.

Borah, J., Baruah, S., Bhargavi, G. et al., “Transmit Antenna Selection for Achieving Energy Efficiency in Massive MIMO Based 5G Cellular Network,” Radioelectron. Commun. Syst., 66, 85–94 (2023). DOI: https://doi.org/10.3103/S0735272723020048

Published

2025-01-22

Issue

Online first articles

Section

Research Articles