Abstract
The Massive multiple-input multiple-output (MIMO) system can schedule dozens of end user equipment at each time slot, however, different quality-of-service (QoS) requirements needs different scheduling policy. Some QoS requirements of buffering services are related to the stability of long term transmit rate, and the instantaneous rate depends on the scheduling policy and channel state. Therefore it is difficult to build direct relationship between the QoS requirement and optimal scheduling user number at each time slot in Massive MIMO system. Based on the effective capacity (EC) theory, the relationship among the number of scheduling user, the QoS requirement and the effective transmit rate is built. The simulation result shows that EC can be described by a smooth function of the number of scheduled users and the QoS requirement.
This work is supported in part by the Natural Science Foundation of Jiangsu Province of China (No. BK20161165), the applied fundamental research Foundation of Xuzhou of China (No. KC17072), the Open Fund of the Jiangsu Province Key Laboratory of Intelligent Industry Control Technology, Xuzhou University of Technology. and the Ministry of Housing and Urban-Rural Development Science and Technology Planning Project (2016-R2-060).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Jiang, D., Wang, W., Shiand, L., Song, H.: A compressive sensing-based approach to end-to-end network traffic reconstruction. IEEE Trans. Netw. Sci. Eng. (2018). https://doi.org/10.1109/TNSE.2018.2877597
Jiang, D., Huo, L., Song, H.: Rethinking behaviors and activities of base stations in mobile cellular networks based on big data analysis. IEEE Trans. Netw. Sci. Eng. 1(2), 1–12 (2018)
Jiang, D., Huo, L., Li, Y.: Fine-granularity inference and estimations to network traffic for SDN. Plos One 13(5), 1–23 (2018)
Chen, L., et al.: A lightweight end-side user experience data collection system for quality evaluation of multimedia communications. IEEE Access 6(1), 15408–15419 (2018)
Jiang, D., Zhang, P., Lv, Z., Song, H.: Energy-efficient multi-constraint routing algorithm with load balancing for smart city applications. IEEE Internet Things J. 3(6), 1437–1447 (2018)
Jiang, D., Li, W., Lv, H.: An energy-efficient cooperative multicast routing in multi-hop wireless networks for smart medical applications. Neurocomputing 220(2017), 160–169 (2017)
Jiang, D., Huo, L., Lv, Z., Song, H., Qin, W.: A joint multi-criteria utility-based network selection approach for vehicle-to-infrastructure networking. IEEE Trans. Intell. Transp. Syst. 19(10), 3305–3319 (2018)
Chen, L., Jiang, D., Bao, R., Xiong, J., Liu, F., Bei, L.: MIMO scheduling effectiveness analysis for bursty data service from view of QoE. Chinese J. Electron. 26(5), 1079–1085 (2017)
Abarghouyi, H., Razavizadeh, S.M., Bjornson, E.: QoE-aware beamforming design for massive MIMO heterogeneous networks. IEEE Trans. Veh. Technol. 67(9), 8315–8323 (2018)
Chaudhari, S., Cabric, D.: QoS aware power allocation and user selection in massive MIMO underlay cognitive radio networks. IEEE Trans. Cogn. 4(2), 220–231 (2018)
Gao, X., Edfors, O., Rusek, F., Tufvesson, F.: Massive MIMO performance evaluation based on measured propagation data. IEEE Trans. Wirel. Commun. 14(7), 3899–3911 (2015)
Björnson, E., Larsson, E.G., Debbah, M.: Massive MIMO for maximal spectral efficiency: how many users and pilots should be allocated? IEEE Trans. Wirel. Commun. 15(2), 1293–1308 (2016)
Wu, D., Negi, R.: Effective capacity: a wireless link model for support of quality of service. IEEE Trans. Wirel. Commun. 2(4), 630–643 (2003)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Chen, L., Zhang, L. (2019). Optimal Scheduling User Number in Massive MIMO with QoS Requirement. In: Song, H., Jiang, D. (eds) Simulation Tools and Techniques. SIMUtools 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-030-32216-8_61
Download citation
DOI: https://doi.org/10.1007/978-3-030-32216-8_61
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-32215-1
Online ISBN: 978-3-030-32216-8
eBook Packages: Computer ScienceComputer Science (R0)