Providing a resource scheduling method in the new generation of wireless local networks

Pirhayati, Azadeh; Mohammadi, Reza; Nassiri, Mohammad

doi:10.48301/kssa.2024.468976.2953

Providing a resource scheduling method in the new generation of wireless local networks

Document Type : Original Article

Authors

azadeh pirhayati

reza mohammadi

mohammad nassiri

Department of Computer Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran

10.48301/kssa.2024.468976.2953

Abstract

Due to the rapid growth of communication technologies and services, it is expected that in the coming years, billions of devices will be connected through the internet and wireless networks, and a lot of traffic will be sent and received between them. The sixth generation standard for wireless networks called IEEE 802.11ax or WiFi6 is designed for dense environments. One of the main issues in 6G wireless networks is resource management in dense environments. The increased number of stations and the need for more speed and efficiency have created new challenges in resource scheduling. Among these challenges, we can mention the increase in bandwidth demand, frequency interference, resource limitation, resource scheduling, energy consumption, delay, and maintaining the security of users. Our goal is to present a resource scheduling method to improve the efficiency and productivity of wireless networks in dense and heterogeneous environments that utilize the entire bandwidth space. In this research, a method for resource scheduling at the access point based on the Orthogonal Frequency Division Multiple Access (OFDMA) mechanism is proposed. This method has been evaluated using ns-3 network simulator. The results show the proposed scheduler's better performance in terms of throughput, end-to-end delay, and Head-of-Line delay. As a result, the proposed method can help improve the quality of users' experience in dense and heterogeneous environments.

Keywords

IEEE 802.11ax standard

OFDMA mechanism

Wireless LANs

scheduling

WiFi6

Subjects

network

[1] Bai, J. (2018). Performance Enhancement of IEEE 802.11 AX in Ultra-Dense Wireless Networks [Master’s thesis, The University of Western Ontario]. Canada. https://ir.lib.uwo.ca/etd/5938

[2] Naribole, S., Lee, W. B., & Ranganath, A. (2019). Impact of MU EDCA channel access on IEEE 802.11 ax WLANs. 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 1-5. https://doi.org/10.1109/VTCFall.2019.8891575

[3] Qu, Q., Li, B., Yang, M., Yan, Z., Yang, A., Deng, D.-J., & Chen, K.-C. (2019). Survey and performance evaluation of the upcoming next generation WLANs standard-IEEE 802.11 ax. Mobile Networks and Applications, 24, 1461-1474. https://doi.org/https://doi.org/10.1007/s11036-019-01277-9

[4] Ahadiani, M., Masoudi, O. A., Malaek, S. M. B., & Majidi, N. (2022). Identifying the Drivers and Propellants of IoT Application in the Management of Iran's Aviation Industry. Karafan Quarterly Research Journal, 19, 597-618. https://doi.org/https://doi.org/10.48301/kssa.2022.316253.1870

[5] Karimi, H. (2021). Sensor Node Clustering Algorithm with Respect to Node Density in Wireless Sensor Networks. Karafan Quarterly Research Journal, 18(3), 253-272. https://doi.org/https://doi.org/10.48301/kssa.2021.269713.1360

[6] Deypir, M., Maarefi, A., & Zoughi, T. (2024). A Hybrid Multivariate Routing Approach for Improving Efficiency in VANETS. Karafan Quarterly Research Journal, -. https://doi.org/http://doi.org/10.48301/kssa.2024.423334.2752

[7] Bellalta, B. (2016). IEEE 802.11 ax: High-efficiency WLANs. IEEE Wireless Communications, 23(1), 38-46. https://doi.org/https://doi.org/10.1109/MWC.2016.7422404

[8] Filoso, D. G., Kubo, R., Hara, K., Tamaki, S., Minami, K., & Tsuji, K. (2020). Proportional-based resource allocation control with QoS adaptation for IEEE 802.11 ax. ICC 2020-2020 IEEE International Conference on Communications (ICC), 1-6. https://doi.org/https://doi.org/10.1109/ICC40277.2020.9149111

[9] Mozaffariahrar, E., Theoleyre, F., & Menth, M. (2022). A survey of Wi-Fi 6: Technologies, advances, and challenges. Future Internet, 14(10), 293. https://doi.org/https://doi.org/10.3390/fi14100293

[10] Ibrahim Masri, E. E., & Ergüzen, A. (2020). Review Paper on 802.11 ax Scheduling and Resource Allocation. Int. J. Trend Sci. Res. Dev.(IJTSRD), 5(1), 1134-1139. https://www.ijtsrd.com/papers/ijtsrd38162.pdf

[11] Sharon, O., & Alpert, Y. (2019). Advanced IEEE 802.11 ax TCP aware scheduling under unreliable channels. International Journal of Communication Systems, 32(14), e4060. https://doi.org/https://doi.org/10.1002/dac.4060

[12] Bankov, D., Didenko, A., Khorov, E., & Lyakhov, A. (2018). OFDMA uplink scheduling in IEEE 802.11 ax networks. 2018 IEEE international conference on communications (ICC), 1-6. https://doi.org/https://doi.org/10.1109/ICC.2018.8422767

[13] Magrin, D., Avallone, S., Roy, S., & Zorzi, M. (2023). Performance Evaluation of 802.11 ax OFDMA through Theoretical Analysis and Simulations. IEEE Transactions on Wireless Communications, 22(8), 5070-5083. https://doi.org/https://doi.org/10.1109/TWC.2022.3231447

[14] Yang, M., Li, B., & Yan, Z. (2021). MAC Technology of IEEE 802.11 ax: Progress and Tutorial. Mobile Networks and Applications, 26, 1122-1136. https://doi.org/https://doi.org/10.1007/s11036-020-01622-3

[15] Avdotin, E., Bankov, D., Khorov, E., & Lyakhov, A. (2019). OFDMA resource allocation for real-time applications in IEEE 802.11 ax networks. 2019 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom), 1-3. https://doi.org/https://doi.org/10.1109/BlackSeaCom.2019.8812774

[16] Deng, D.-J., Lin, Y.-P., Yang, X., Zhu, J., Li, Y.-B., Luo, J., & Chen, K.-C. (2017). IEEE 802.11 ax: highly efficient WLANs for intelligent information infrastructure. IEEE Communications Magazine, 55(12), 52-59. https://doi.org/https://doi.org/10.1109/MCOM.2017.1700285

[17] Islam, G. Z., & Kashem, M. A. (2022). Efficient resource allocation in the IEEE 802.11 ax network leveraging OFDMA technology. Journal of King Saud University-Computer and Information Sciences, 34(6), 2488-2496. https://doi.org/http://dx.doi.org/10.1016/j.jksuci.2020.10.019

[18] Magrin, D., Avallone, S., Roy, S., & Zorzi, M. (2021). Validation of the ns-3 802.11ax OFDMA implementation. Proceedings of the 2021 Workshop on ns-3, 1–8. https://doi.org/https://doi.org/10.1145/3460797.3460798

[19] Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on selected areas in communications, 18(3), 535-547. https://doi.org/https://doi.org/10.1109/49.840210

[20] Bellalta, B., & Kosek-Szott, K. (2019). AP-initiated multi-user transmissions in IEEE 802.11 ax WLANs. Ad Hoc Networks, 85, 145-159. https://doi.org/https://doi.org/10.48550/arXiv.1702.05397

[21] Dovelos, K., & Bellalta, B. (2020). A scheduling policy for downlink OFDMA in IEEE 802.11 ax with throughput constraints. arXiv preprint arXiv:2009.00413. https://doi.org/https://doi.org/10.48550/arXiv.2009.00413

[22] Piro, G., Grieco, L. A., Boggia, G., Fortuna, R., & Camarda, P. (2011). Two-level downlink scheduling for real-time multimedia services in LTE networks. IEEE Transactions on Multimedia, 13(5), 1052-1065. https://doi.org/https://doi.org/10.1109/TMM.2011.2152381

[23] Afaqui, M. S., Garcia-Villegas, E., Lopez-Aguilera, E., Smith, G., & Camps, D. (2015). Evaluation of dynamic sensitivity control algorithm for IEEE 802.11 ax. 2015 IEEE wireless communications and networking conference (WCNC), 1060-1065. https://doi.org/https://doi.org/10.1109/WCNC.2015.7127616

[24] Bankov, D., Didenko, A., Khorov, E., Loginov, V., & Lyakhov, A. (2017). IEEE 802.11 ax uplink scheduler to minimize, delay: A classic problem with new constraints. 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), 1-5. https://doi.org/https://doi.org/10.1109/PIMRC.2017.8292382

[25] Dovelos, K., & Bellalta, B. (2018). Optimal resource allocation in IEEE 802.11 ax uplink OFDMA with scheduled access. arXiv preprint arXiv:1811.00957. https://doi.org/https://doi.org/10.48550/arXiv.1811.00957

[26] Bhattarai, S., Naik, G., & Park, J.-M. J. (2019). Uplink resource allocation in IEEE 802.11 ax. ICC 2019-2019 IEEE international conference on communications (ICC), 1-6. https://doi.org/https://doi.org/10.1109/ICC.2019.8761594

[27] Bai, J., Fang, H., Suh, J., Aboul-Magd, O., Au, E., & Wang, X. (2018). Adaptive uplink OFDMA random access grouping scheme for ultra-dense networks in IEEE 802.11 ax. 2018 IEEE/CIC International Conference on Communications in China (ICCC), 34-39. https://doi.org/https://doi.org/10.1109/ICCChina.2018.8641202

[28] Avallone, S., Imputato, P., Redieteab, G., Ghosh, C., & Roy, S. (2021). Will OFDMA improve the performance of 802.11 WiFi networks? IEEE Wireless Communications, 28(3), 100-107. https://doi.org/https://doi.org/10.1109/MWC.001.2000332

[29] Park, H. (2021). Performance analysis of trigger frame in enhanced UL and DL MU MIMO transmissions. World Wide Web, 24(5), 1533-1550. https://doi.org/https://doi.org/10.1007/s11280-021-00921-3

[30] Peng, M., Yin, Q., Zhang, K., & Kai, C. (2023). Adaptive multi-user uplink resource allocation based on access delay analysis in IEEE 802.11 ax. Wireless Networks, 29(3), 1223-1235. https://doi.org/https://doi.org/10.1007/s11276-022-03192-6

[31] Henderson, T. R., Lacage, M., Riley, G. F., Dowell, C., & Kopena, J. (2008). Network simulations with the ns-3 simulator. SIGCOMM demonstration, 14(14), 527. http://conferences.sigcomm.org/sigcomm/2008/papers/p527-hendersonA.pdf