TY - GEN
T1 - Evaluation of User Allocation Techniques in Massive MIMO 5G Networks
AU - Bouras, Christos
AU - Diasakos, Damianos
AU - Gkamas, Apostolos
AU - Kokkinos, Vasileios
AU - Pouyioutas, Philippos
AU - Prodromos, Nikolaos
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Massive MIMO (Multiple Input Multiple Output) is a fundamental technique for improving the efficiency of 5G wireless networks. At the base station, it calls for the use of numerous antennas - usually in the dozens or even hundreds. In addition to better coverage and less interference, this enables a large increase in the amount of data that can be delivered and received simultaneously. By enabling more precise signal transmission and reception, Massive MIMO can also result in significant energy savings. The use of optimization techniques can further improve the performance of 5G networks. The aim of this paper is to investigate a signal quality optimization technique for MIMO in which users are allocated to antennas according to different algorithms. For our research, the DeepMIMO simulator produced a dataset that sets up all necessary parameters. In our study, we examine different techniques for user allocation in 5G MIMO Networks. We conclude that transforming the problem of user allocation to a linear assignment problem in order to find the most efficient connection between the users and the base stations is one of the best ways to optimize user allocation.
AB - Massive MIMO (Multiple Input Multiple Output) is a fundamental technique for improving the efficiency of 5G wireless networks. At the base station, it calls for the use of numerous antennas - usually in the dozens or even hundreds. In addition to better coverage and less interference, this enables a large increase in the amount of data that can be delivered and received simultaneously. By enabling more precise signal transmission and reception, Massive MIMO can also result in significant energy savings. The use of optimization techniques can further improve the performance of 5G networks. The aim of this paper is to investigate a signal quality optimization technique for MIMO in which users are allocated to antennas according to different algorithms. For our research, the DeepMIMO simulator produced a dataset that sets up all necessary parameters. In our study, we examine different techniques for user allocation in 5G MIMO Networks. We conclude that transforming the problem of user allocation to a linear assignment problem in order to find the most efficient connection between the users and the base stations is one of the best ways to optimize user allocation.
KW - allocation and scheduling
KW - beamforming
KW - massive MIMO
KW - Resource management
KW - smart antennas: MIMO
UR - http://www.scopus.com/inward/record.url?scp=85179512444&partnerID=8YFLogxK
U2 - 10.1109/WINCOM59760.2023.10322955
DO - 10.1109/WINCOM59760.2023.10322955
M3 - Conference contribution
AN - SCOPUS:85179512444
T3 - Proceedings - 10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023
BT - Proceedings - 10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023
A2 - Ibrahimi, Khalil
A2 - El Kamili, Mohamed
A2 - Kobbane, Abdellatif
A2 - Shayea, Ibraheem
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023
Y2 - 26 October 2023 through 28 October 2023
ER -