Abstract
The Fourth Generation (4G) wireless communication network is widely implemented with standardized framework of operation and QoS constraints. Emergence of enhanced mobile broadband (eMBB) and user demand for ultra-reliable and low latency communication, research interests are now shifted to the Fifth Generation (5G) network. With rapid increase in number of mobile devices and associated user’s demand of diverse services, the 5G network is expected to improve overall spectrum efficiency. However, latency, energy efficiency, QoS, throughput, are some of the challenges to be addressed for a reliable network. The chapter discusses congestion control algorithms and delay bounded QoS provisioning framework. This QoS provisioning can be deployed in LTE 4G and 5G network with differential baud rate and fading parameters. Hybrid scheduling with QoS class identifier is discussed for LTE access network.
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Sharma, T., Chehri, A., Fortier, P.: Review of optical and wireless backhaul networks and emerging trends of next generation 5G and 6G technologies. Trans. Emerg. Telecommun. Technol. 32(3), 1–16 (2021). https://doi.org/10.1002/ett.4155
Abdalla, I., Venkatesan, S.: A QoE preserving M2M-aware hybrid scheduler for LTE uplink. In: International Conference on Selected Topics in Mobile and Wireless Networking (MoWNeT), vol. 7, pp. 127–132 (2013). https://doi.org/10.1109/MoWNet.2013.6613808
Akhtar, T., Tselios, C., Politis, I.: Radio resource management: approaches and implementations from 4G to 5G and beyond. 27(1) (2021)
Tang, J., Zhang, X.: Quality-of-service driven power and rate adaptation for multichannel communications over wireless links. IEEE Trans. Wirel. Commun. 6(12), 4349–4360 (2007). https://doi.org/10.1109/TWC.2007.06031
Inaba, T., Sakamoto, S., Oda, T., Barolli, L., Takizawa, M.: A new FACS for cellular wireless networks considering QoS: a comparison study of FuzzyC with MATLAB. In: Proceedings of the 18th International Conference on Network-Based Information Systems. NBiS 2015, pp. 338–344 (2015). https://doi.org/10.1109/NBiS.2015.52
Beshley, M., Kryvinska, N., Seliuchenko, M., Beshley, H., Shakshuki, E.M., Yasar, A.U.H.: End-to-end QoS ‘Smart Queue’ management algorithms and traffic prioritization mechanisms for narrow-band internet of things services in 4G/5G networks. Sensors (Switzerland) 20(8) (2020). https://doi.org/10.3390/s20082324
Haile, H., Grinnemo, K.J., Ferlin, S., Hurtig, P., Brunstrom, A.: End-to-end congestion control approaches for high throughput and low delay in 4G/5G cellular networks. Comput. Networks 186, 107692 (2021). https://doi.org/10.1016/j.comnet.2020.107692
Beshay, J.D., Nasrabadi, A.T., Prakash, R., Francini, A.: Link-coupled TCP for 5G networks. In: IEEE/ACM 25th International Symposium on Quality of Service (IWQoS) (2017). https://doi.org/10.1109/IWQoS.2017.7969170
Zhu, G., Zan, J., Yang, Y., Qi, X.: A supervised learning based QoS assurance architecture for 5G networks. IEEE Access 7, 43598–43606 (2019). https://doi.org/10.1109/ACCESS.2019.2907142
Park, S., Lee, J., Kim, J., Lee, J., Lee, K.: ExLL: an extremely low-latency congestion control for mobile cellular networks. In: CoNEXT 2020: Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies, pp. 307–319 (2020)
Zhang, X., Wang, J., Poor, H.V.: Heterogeneous statistical-QoS driven resource allocation over mmWave massive-MIMO based 5G mobile wireless networks in the non-asymptotic regime. IEEE J. Sel. Areas Commun. 37(12), 2727–2743 (2019). https://doi.org/10.1109/JSAC.2019.2947941
Xie, Y., Yi, F., Jamieson, K.: PBE-CC: congestion control via endpoint-centric, physical-layer bandwidth measurements. In: SIGCOMM 2020: Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication on the Applications, Technologies, Architectures, and Protocols for Computer Communication, pp. 451–464 (2020). https://doi.org/10.1145/3387514.3405880
Haile, H., Grinnemo, K.J., Ferlin, S., Hurtig, P., Brunstrom, A.: End-to-end congestion control approaches for high throughput and low delay in 4G/5G cellular networks. Comput. Networks 186, 107692 (2021). https://doi.org/10.1016/j.comnet.2020.107692
Chen, J., et al.: SDATP: an SDN-based traffic-adaptive and service-oriented transmission protocol. IEEE Trans. Cogn. Commun. Netw. 6(2), 756–770 (2020). https://doi.org/10.1109/TCCN.2019.2963149
Sharma, T., Chehri, A., Fortier, P.: Review of optical and wireless backhaul networks and emerging trends of next generation 5G and 6G technologies. Trans. Emerg. Telecommun. Technol. 32(3), 1–16 (2021). https://doi.org/10.1002/ett.4155
Ahmad, W.S.H.M.W., et al.: 5G technology: towards dynamic spectrum sharing using cognitive radio networks. IEEE Access 8, 14460–14488 (2020). https://doi.org/10.1109/ACCESS.2020.2966271
Abbasloo, S., Li, T., Xu, Y., Chao, H.J.: Cellular controlled delay TCP (C2TCP). In: IFIP Networking Conference (IFIP Networking) and Workshops, pp 118–126 (2018). https://doi.org/10.23919/IFIPNetworking.2018.8696844
Azzino, T., Drago, M., Polese, M., Zanella, A., Zorzi, M.: X-TCP: a cross layer approach for TCP uplink flows in mmwave networks. In: 16th Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net), pp. 1–6 (2017). https://doi.org/10.1109/MedHocNet.2017.8001650
Na, W., Bae, B., Cho, S., Kim, N.: DL-TCP: deep learning-based transmission control protocol for disaster 5G mmWave networks. IEEE Access 7, 145134–145144 (2019). https://doi.org/10.1109/ACCESS.2019.2945582
Jiang, H., Wang, Y., Lee, K., Rhee, I.: DRWA: a receiver-centric solution to bufferbloat in cellular networks. IEEE Trans. Mob. Comput. 15(11), 2719–2734 (2016). https://doi.org/10.1109/TMC.2015.2510641
Lu, F., Du, H., Jain, A., Voelker, G.M., Snoeren, A.C., Terzis, A.: CQIC: revisiting cross-layer congestion control for cellular networks. In: HotMobile 2015: Proceedings of the 16th International Workshop on Mobile Computing Systems and Applications, pp. 45–50 (2015). https://doi.org/10.1145/2699343.2699345
Li, W., Zhou, F., Chowdhury, K.R., Meleis, W.M.: QTCP: adaptive congestion control with reinforcement learning. IEEE Trans. Netw. Sci. Eng. 4697, 1–13 (2018). https://doi.org/10.1109/TNSE.2018.2835758
Zhong, Z., Hamchaoui, I., Ferrieux, A., Khatoun, R., Serhrouchni, A.: CDBE: a cooperative way to improve end-to-end congestion control in mobile network. In: International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob), vol. 2018, pp. 216–223 (2018). https://doi.org/10.1109/WiMOB.2018.8589175
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Nath, R. (2023). QoS Aware Service Provisioning and Resource Distribution in 4G/5G Heterogeneous Networks. In: Kadyan, V., Singh, T.P., Ugwu, C. (eds) Deep Learning Technologies for the Sustainable Development Goals. Advanced Technologies and Societal Change. Springer, Singapore. https://doi.org/10.1007/978-981-19-5723-9_3
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DOI: https://doi.org/10.1007/978-981-19-5723-9_3
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