Abstract
A base station (BS) of the fifth generation (5G) cellular system can operate in high frequency band to obtain more bandwidth. The beamforming technology is a promising technique to relieve issues when operating in high frequency band. In this work, we assume that the BS equips with hybrid beamforming capability. Before disseminating downlink data to UEs, in every transmission time interval (TTI), the BS selects a set of user equipments (UEs), assigns radio resource blocks (RBs), and adjusts its analog and digital beamforming components. In this paper, we focus on designing medium access controller (MAC) layer approaches to assign radio resource to UEs. First, we formulate a linear programming formulation, which goal is to maximize network throughput. We then design an optimized solution to achieve the goal. However, when maximizing throughput, some UEs may be starved, and their downlink packets will be dropped due to the delay limit constraints of their downlink traffic flows. So, we further design a formulation to achieve fair scheduling with quality of service (QoS) considerations. We design a system profit model to facilitate fair radio resource scheduling. The simulation results indicate that the proposed solutions can indeed increase system throughput and reduce packet drop ratio.
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References
Study on new radio access technology physical layer aspects (38.802). 3GPP Technical Report (TR), (2017).
5G; NR; Physical channels and modulation (38.211). 3GPP Technical Specification (TS), (2018).
5G; NR; Physical layer procedures for control (38.213). 3GPP Technical Specification (TS) (2018).
System Architecture for the 5G System (23.501). 3GPP Technical Specification (TS), (2018).
Ahmed, I., & Khammari, H. (2018). Joint machine learning based resource allocation and hybrid beamforming design for massive MIMO systems. In Proceedings of the IEEE Globecom Workshops.
Berraki, D. E., Armour, S. M. D., & Nix, A. R. (2014). Codebook based beamforming and multiuser scheduling scheme for mmWave outdoor cellular systems in the 28, 38 and 60GHz bands. In Proceedings of the IEEE Globecom Workshops.
Chen, Y., Wu, H., & Liu, D. (2019). Beam search assisted user scheduling for mmWave hybrid beamforming systems. In Proceedings of the International Conference on Computing, Communications and IoT Applications (ComComAp), pages 76–81.
Du, J., Xu, W., Zhao, C., & Vandendorpe, L. (2018). Hybrid beamforming design for multiuser massive MIMO-OFDM systems. In Proceedings of the IEEE International Symposium on Wireless Communication Systems (ISWCS).
Dutta, S., Mezzavilla, M., Ford, R., Zhang, M., Rangan, S., & Zorzi, M. (2017). Frame structure design and analysis for millimeter wave cellular systems. IEEE Transactions on Wireless Communications, 16(3), 1508–1522.
Esswie, A. A., & Pedersen, K. I. (2018). Multi-user preemptive scheduling for critical low latency communications in 5G networks. In Proceedings of the IEEE Symposium on Computers and Communications (ISCC).
Fan, J., Yin, Q., Li, G. Y., Peng, B., & Zhu, X. (2011). Adaptive block-level resource allocation in OFDMA networks. IEEE Transactions on Wireless Communications, 10(11), 3966–3972.
Femenias, G., Riera-Palou, F., Mestre, X., & Olmos, J. J. (2017). Downlink scheduling and resource allocation for 5G MIMO-multicarrier: OFDM vs FBMC/OQAM. IEEE Access, 5, 13770–13786.
Gante, J., Falciao, G., & Sousa, L. (2018). Data-aided fast beamforming selection for 5G. In Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
He, S., Wu, Y., Ng, D. W. K., & Huang, Y. (2017). Joint optimization of analog beam and user scheduling for millimeter wave communications. IEEE Communications Letters, 21(12), 2638–2641.
Hegde, G., Masouros, C., & Pesavento, M. (2018). Analog beamformer design for interference exploitation based hybrid beamforming. In Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM).
Jayaprakasam, S., Ma, X., Choi, J. W., & Kim, S. (2017). Robust beam-tracking for mmWave mobile communications. IEEE Communications Letters, 21(12), 2654–2657.
Jiang, Z., Chen, S., Zhou, S., & Niu, Z. (2018). Joint user scheduling and beam selection optimization for beam-based massive MIMO downlinks. IEEE Transactions on Wireless Communications, 17(4), 2190–2204.
Kela, P., Puttonen, J., Kolehmainen, N., Ristaniemi, T., Henttonen, T. & Moisio, M. (2008). Dynamic packet scheduling performance in UTRA long term evolution downlink. In Proceedings of the IEEE International Symposium on Wireless Pervasive Computing (ISWPC).
Kushner, H. J., & Whiting, P. A. (2004). Convergence of proportional-fair sharing algorithms under general conditions. IEEE Transactions on Wireless Communications, 3(4), 1250–1259.
Kutty, S., & Sen, D. (2015). Beamforming for millimeter wave communications: An inclusive survey. IEEE Communications Surveys & Tutorials, 18(2), 949–973.
Mo, J., Ng, B. L., Chang, S., Huang, P., Kulkarni, M. N., Alammouri, A., Zhang, J. C., Lee, J., & Choi, W.-J. (2019). Beam codebook design for 5G mmWave terminals. IEEE Access, 7.
Polese, M., Giordani, M., Mezzavilla, M., Rangan, S., & Zorzi, M. (2017). Improved handover through dual connectivity in 5G mmWave mobile networks. IEEE Journal on Selected Areas in Communications, 35(9), 2069–2084.
Qiao, J., Shen, X., Mark, J. W., & He, Y. (2015). MAC-layer concurrent beamforming protocol for indoor millimeter-wave networks. IEEE Transactions on Vehicular Technology, 64(1), 327–338.
Ramalingam M. (2018). 5G NR Beam Management and Beam Scheduling (everything about the beams). https://www.linkedin.com/pulse/5g-nr-beam-management-scheduling-everything-beams-ramalingam/.
Rhee, J.-H., Holtzman, J., & Kim, D.-K. (2003). Scheduling of real/non-real time services: adaptive EXP/PF algorithm. In Proceedings of the IEEE Vehicular Technology Conference (VTC-Spring).
Sohrabi, F., & Yu, W. (2017). Hybrid analog and digital beamforming for mmWave OFDM large-scale antenna arrays. IEEE Journal on Selected Areas in Communications, 35(7), 1432–1443.
Va, V., Vikalo, H., & Heath, R. W. (2016). Beam tracking for mobile millimeter wave communication systems. In IEEE Global Conference on Signal and Information Processing (GlobalSIP).
Viswanath, P., Tse, D. N. C., & Laroia, R. (2002). Opportunistic beamforming using dumb antennas. IEEE Transactions on Information Theory, 48(6), 1277–1294.
Vora, A. & Kang, K.-D. (2018). Downlink scheduling and resource allocation for 5G MIMO multicarrier systems. In Proceedings of the IEEE 5G World Forum (5GWF).
Wang, J., Lan, Z., woo Pyo, C., Baykas, T., sean Sum, C., Rahman, M., Gao, J., Funada, R., Kojima, F., Harada, H., & Kato, S. (2009). Beam codebook based beamforming protocol for multi-gbps millimeter-wave wpan systems. IEEE Journal on Selected Areas in Communications, 27(8), 1390–1399.
Wang, Y.-C., & Hsieh, S.-Y. (2016). Service-differentiated downlink flow scheduling to support QoS in long term evolution. Computer Networks, 94, 344–359.
Xie, Z., & Chen, W. (2019). A joint channel and queue aware scheduling method for multi-user massive MIMO systems. In Proceedings of the IEEE International Conference on Communications (ICC).
Xu, C., Liu, S., Zhang, C., Huang, Y., & Yang, L. (2020). Joint user scheduling and beam selection in mmWave networks based on multi-agent reinforcement learning. In Proceedings of the IEEE International Sensor Array and Multichannel Signal Processing Workshop (SAM).
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Cho, CW., Pan, MS. Downlink radio resource scheduling for OFDMA systems with hybrid beamforming. Wireless Netw 28, 273–286 (2022). https://doi.org/10.1007/s11276-021-02836-3
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DOI: https://doi.org/10.1007/s11276-021-02836-3