Wireless Networks

, Volume 25, Issue 8, pp 5083–5097 | Cite as

A spatial clustering group division-based OFDMA access protocol for the next generation WLAN

  • Yong Li
  • Bo Li
  • Mao YangEmail author
  • Zhongjiang Yan


The next generation wireless local area network (WLAN) needs to significantly improve the area throughput in high-dense deployment scenario. Orthogonal frequency division multiple access (OFDMA), considered as the key technology of the next generation WLAN, has been adopted by IEEE 802.11ax. However, most existing studies have one tricky problem: interference extension problem, i.e., the stations (STAs) placed at dispersive locations from one basic service set (BSS) access channel and transmit data simultaneously through OFDMA, thereby interfering a large area and suppressing the potential transmissions around this BSS. Unfortunately, high-dense deployment scenario exacerbates interference extension problem. This article proposes a spatial clustering group division-based OFDMA (SCGD-OFDMA) protocol, which enables the geographically close STAs to form spatial clustering groups, named SCGs. Each SCG has a leader STA and several member STAs. Each SCG’s leader STA contends for channel resources. After that, the leader STAs that successfully contending channel are scheduled by the access point one by one to trigger its member STAs to transmit uplink data by using OFDMA. Therefore, the geographical interference area is reduced and the area throughput is improved since the concurrent STAs in one SCG are located in limited area. This article theoretically analyzes the optimal SCG establishment, and throughput and area throughput of SCGD-OFDMA. Theoretical analysis is consistent with simulation results. The simulation results also show that when the number of STAs is 200 and all resource units are used for random access, SCGD-OFDMA outperforms IEEE 802.11ax and OMAX in area throughput by 56.13% and 190.97%, respectively.


Spatial clustering group High-dense deployment scenario Medium access control OFDMA The next generation WLAN 



This work was supported in part by the National Natural Science Foundations of CHINA (Grant No. 61501373, No. 61771390, No. 61771392, and No. 61271279), the National Science and Technology Major Project (Grant No. 2016ZX03001018-004), and Science and Technology on Avionics Integration Laboratory (20185553035).


  1. 1.
    Sun, W., et al. (2014). Wi-Fi could be much more. IEEE Communications Magazine, 52(11), 22–29.CrossRefGoogle Scholar
  2. 2.
    Bellalta, B. (2016). IEEE 802.11ax: High-efficiency WLANS. IEEE Wireless Communications, 23(1), 38–46.CrossRefGoogle Scholar
  3. 3.
    Deng, D. J., et al. (2017). IEEE 802.11ax: Highly efficient WLANs for intelligent information infrastructure. IEEE Communications Magazine, 55(12), 52–59.CrossRefGoogle Scholar
  4. 4.
    Gallo, P., Kosek-Szott, K., Szott, S., & Tinnirello, I. (2018). CADWAN: A control architecture for dense WiFi access networks. IEEE Communications Magazine, 56(1), 194–201.CrossRefGoogle Scholar
  5. 5.
    Li, B., Qu, Q., Yan, Z., & Yang, M. (2015). Survey on OFDMA based MAC protocols for the next generation WLAN. In 2015 IEEE wireless communications and networking conference workshops (WCNCW), New Orleans, LA, 2015 (pp. 131–135).Google Scholar
  6. 6.
    Qu, Q., Li, B., Yang, M., & Yan, Z. (2015). An OFDMA based concurrent multiuser MAC for upcoming IEEE 802.11ax. In 2015 IEEE wireless communications and networking conference workshops (WCNCW), New Orleans, LA, 2015 (pp. 136–141).Google Scholar
  7. 7.
    Cisco. (2018, February). Global mobile data traffic forecast update, Cisco Visual Networking Index: White Paper. Accessed 26 Feb 2018.
  8. 8.
    Yang, M., Li, B., Bai, Z., et al. (2018). SGMA: Semi-granted multiple access for non-orthogonal multiple access (NOMA) in 5G networking. Journal of Network and Computer Applications, 112, 115–125.CrossRefGoogle Scholar
  9. 9.
    Karaca, M., Bastani, S., & Landfeldt, B. (2017). Modifying backoff freezing mechanism to optimize dense IEEE 802.11 networks. IEEE Transactions on Vehicular Technology, 66(10), 9470–9482.CrossRefGoogle Scholar
  10. 10.
    Afaqui, M. S., Garcia-Villegas, E., & Lopez-Aguiler, E. A. (2017). IEEE 802.11ax: Challenges and requirements for future high efficiency WiFi. IEEE Wireless Communications, 24(3), 130–137.CrossRefGoogle Scholar
  11. 11.
    IEEE 802.11 working group of the LAN/MAN standards committee of the IEEE computer society. (2019). IEEE 802.11ax proposed draft 4.0. Accessed 10 July 2019.
  12. 12.
    Jung, J., & Lim, J. (2012). Group contention-based OFDMA MAC protocol for multiple access interference-free in WLAN systems. IEEE Transactions on Wireless Communications, 11(2), 648–658.CrossRefGoogle Scholar
  13. 13.
    Deng, D. J., Lien, S. Y., Lee, J., & Chen, K. C. (2016). On quality-of-service provisioning in IEEE 802.11ax WLANs. IEEE Access, 4, 6086–6104.CrossRefGoogle Scholar
  14. 14.
    Lee, J., & Kim, C. (2017). An efficient multiple access coordination scheme for OFDMA WLAN. IEEE Communications Letters, 21(3), 596–599.CrossRefGoogle Scholar
  15. 15.
    Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY) specifications. In IEEE P802.11ax draft 1.2 (2017, April).Google Scholar
  16. 16.
    IEEE 802.11 Task group AX. Status of project IEEE 802.11ax high efficiency WLAN (HEW) accessed (2015, July). Accessed 10 May 2018.
  17. 17.
    Deng, D. J., Chen, K. C., & Cheng, R. S. (2014). IEEE 802.11ax: Next generation wireless local area networks. In 10th international conference on hetero-geneous networking for quality, reliability, security and robustness, 2014 (pp. 77–82).Google Scholar
  18. 18.
    Qu, Q., Li, B., & Yang, M., et al. (2018). Survey and performance evaluation of the upcoming next generation WLAN standard-IEEE 802.11 ax (pp. 1–155) (2018). arXiv preprint arXiv:1806.05908.
  19. 19.
    IEEE 802.11ax Task Group, IEEE P802.11ax D2.0. Telecommunications and information exchange between systems Local and metropolitan area networks—Specific requirements (pp. 1–596) (2017).Google Scholar
  20. 20.
    Li, Y., Li, B., Yang, M., & Yan, Z. (2017). Spatial clustering group based OFDMA multiple access scheme for the next generation WLAN. In 3rd EAI international conference on IoT as a service (IoTaaS 2017), Taiwan, 2017 (pp. 1–8).Google Scholar
  21. 21.
    Kwon, H., Seo, H., Kim, S., & Lee, B. G. (2009). Generalized CSMA/CA for OFDMA systems: Protocol design, throughput analysis, and implementation issues. IEEE Transactions on Wireless Communications, 8(8), 4176–4187.CrossRefGoogle Scholar
  22. 22.
    Kwon, H., Kim, S., & Lee, B. G. (2010). Opportunistic multi-channel CSMA protocol for OFDMA systems. IEEE Transactions on Wireless Communications, 9(5), 1552–1557.CrossRefGoogle Scholar
  23. 23.
    Wang, X., & Wang, H. (2010). A novel random access mechanism for OFDMA wireless networks. In 2010 IEEE global telecommunications conference GLOBECOM 2010, Miami, FL (pp. 1–5).Google Scholar
  24. 24.
    Ferdous, H. S., & Murshed, M. (2010). Enhanced IEEE 802.11 by integrating multiuser dynamic OFDMA. In Wireless telecommunications symposium (WTS), IEEE, 2010 (pp. 1–6).Google Scholar
  25. 25.
    Lou, H., Wang, X., Fang, J., Ghosh, M., Zhang, G., & Olesen, R. (2014). Multi-user parallel channel access for high efficiency carrier grade wireless LANs. In 2014 IEEE international conference on communications (ICC), Sydney, NSW (pp. 3868–3870).Google Scholar
  26. 26.
    Kamoun, M., Mazet, L., & Gault, S. (2009). Efficient backward compatible allocation mechanism for multi-user CSMA/CA schemes. In 2009 first international conference on communications and networking, Hammamet, 2009 (pp. 1–6).Google Scholar
  27. 27.
    Mishima, T., Miyamoto, S., Sampei, S., & Jiang, W. (2013). Novel DCF-based multi-user MAC protocol and dynamic resource allocation for OFDMA WLAN systems. In 2013 international conference on computing, networking and communications (ICNC), San Diego, CA, 2013 (pp. 616–620).Google Scholar
  28. 28.
    Park, J., & Kim, K. S. (2018). Load-balancing scheme with small-cell cooperation for clustered heterogeneous cellular networks. IEEE Transactions on Vehicular Technology, 67(1), 633–649.CrossRefGoogle Scholar
  29. 29.
    Ren, M., Zhang, J., Khoukhi, L., et al. (2018). A unified framework of clustering approach in vehicular ad hoc networks. IEEE Transactions on Intelligent Transportation Systems, 19(5), 1401–1414.CrossRefGoogle Scholar
  30. 30.
    Cooper, C., Franklin, D., Ros, M., et al. (2017). A comparative survey of VANET clustering techniques. In IEEE communications surveys and tutorials (Vol. 19, No. 1, pp. 657–681). Firstquarter 2017.CrossRefGoogle Scholar
  31. 31.
    Ahmad, M., Hameed, A., Ikram, A. A., et al. (2019). State-of-the-art clustering schemes in mobile ad hoc networks: Objectives, challenges, and future directions. IEEE Access, 7, 17067–17081.CrossRefGoogle Scholar
  32. 32.
    Chen, H., Chuang, C., Wang, Y., et al. (2016). Design and implementation of a Cluster-based channel assignment in high density 802.11 WLANs. In 2016 18th Asia-pacific network operations and management symposium (APNOMS).Kanazawa, 2016 (pp. 1–5).Google Scholar
  33. 33.
    Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3), 535–547.CrossRefGoogle Scholar
  34. 34.
    Lin, W., et al. (2016). Integrated link-system level simulation platform for the next generation WLAN—IEEE 802.11ax. In 2016 IEEE global communications conference (GLOBECOM), Washington, DC, 2016 (pp. 1–7).Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Electronics and InformationNorthwestern Polytechnical UniversityXi’anChina
  2. 2.School of Electronics and InformationNorthwestern Polytechnical UniversityXi’anChina

Personalised recommendations