Abstract
5G base stations (BS) distribute resources to User Equipments (UEs) by dividing the BS’s spectrum into sub-channels of different sizes, and then allocate them to UE’s flows for uploading or downloading data based on time length, which may be a long or short duration. In a 4G-network BS, the spectrum of a resource block (RB) is 180 kHz, while in 5G, a BS spectrum is divided into numerologies, the size of which may be: 15, 30, 60, 120, and 240 kHz. The BS algorithm Scheduling and Resource Allocation (SRA) algorithms implemented in this study include Proportional Fairness (PF), Maximum-Largest Weighted Delay First (M-LWDF) and Exponential/Proportional Fairness (EXP/PF). We evaluate the performance of these algorithms in handling different types of packets, e.g., Real-Time (RT) flow, Non-Real-Time (NRT) flow, etc. The SRA algorithms are developed in the 5G-air-simulator, which is an open source C++-based simulator, to deliver eMBB, uRLLC and mMTC packets for analyzing performance of different applications. The parameters used include BS transmission speed, flow size, etc. The metrics parameters include packet delays and transmission fairness, etc. The goal is to use the most suitable SRA to transmit different types of packets for building independent network slices with different service characteristics.
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References
Vora, A., Kang, K.-D.: Effective 5G wireless downlink scheduling and resource allocation in cyber-physical systems. Technologies 6(4), 1–20 (2018)
Abdel-Hadi, A., Clancy, C.: A utility proportional fairness approach for resource allocation in 4G-LTE. In: International Conference on Computing, Networking and Communications (ICNC), Honolulu, HI, USA, pp. 1034–1040 (2014). https://doi.org/10.1109/ICCNC.2014.6785480
Capozzi, F., Piro, G., Grieco, L.A., Boggia, G., Camarda, P.: Downlink packet scheduling in LTE cellular networks: key design issues and a survey. IEEE Commun. Surv. Tutor. 15, 678–700 (2012)
Xian, Y.J., Tian, F.C., Xu, C.B., Yang, Y.: Analysis of M-LWDF fairness and an enhanced M-LWDF packet scheduling mechanism. J. China Univ. Posts Telecommun. 18(4), 82–88 (2011)
Basukala, R., Ramli, H.A.M., Sandrasegaran, K.: Performance analysis of EXP/PF and M-LWDF in downlink 3GPP LTE system. In: First Asian Himalayas International Conference on Internet, Kathmundu, Nepal, pp. 1–5 (2009)
Martiradonna, S., Grassi, A., Piro, G.: 5G-air-simulator: an open-source tool modeling the 5G air interface. Comput. Netw. 177, 107314 (2020)
Kawser, M., Farid, H., Hasin, A., Sadik, A., Razu, I.: Performance comparison between round robin and proportional f air scheduling methods for LTE. Int. J. Inf. Electron. Eng. 2, 678–681 (2012). https://doi.org/10.7763/IJIEE.2012.V2.186
Hao, G.: Predictor antenna systems: exploiting channel state information for vehicle communications. Thesis of Chalmers University of Technology, Sweden, May 2020. arXiv: abs/2005.09758
Luo, C., Ji, J., Wang, Q., Chen, X., Li, P.: Channel state information prediction for 5G wireless communications: a deep learning approach. IEEE Trans. Netw. Sci. Eng. 7(1), 227–236 (2020). https://doi.org/10.1109/TNSE.2018.2848960
Acknowledgments
This study is financial support in part by Ministry of Science and Technology, Taiwan under the grants MOST 108-2221-E-029-009 and MOST 109-2221-E-029-017-MY2.
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Jian, YC., Chung, MS., Susanto, H., Leu, F.Y. (2022). 5G Base Station Scheduling. In: Barolli, L. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2022. Lecture Notes in Networks and Systems, vol 496. Springer, Cham. https://doi.org/10.1007/978-3-031-08819-3_33
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DOI: https://doi.org/10.1007/978-3-031-08819-3_33
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