Data Rate-Aware Predictive Inter-Cell Handoff Technique for IEEE 802.11 Wireless Networks

Authors

https://doi.org/10.48314/isti.vi.57

Abstract

Seamless handoff remains a critical challenge in IEEE 802.11 wireless networks, particularly in dense and highly mobile environments where conventional reactive handoff mechanisms based primarily on Received Signal Strength (RSS) may trigger decisions only after significant degradation in link quality. Recent studies have demonstrated the potential of Machine Learning (ML), edge computing, and Software-Defined Networking (SDN) to improve handoff prediction, reduce unnecessary handovers, and enhance throughput. However, existing approaches largely emphasize handoff latency, success rate, Signal Strength (SS), or general throughput optimization, while the prediction of impending handoff based on the expected Data Rate (DR) of the serving and neighbouring Access Points (APs) remains insufficiently explored. This limitation is significant because a reduction in RSS does not necessarily imply an immediate deterioration in achievable DR, and an AP with stronger SS may provide lower effective DR because of congestion, interference, channel conditions, or resource utilization. This study therefore presents a predictive inter-cell handoff technique for IEEE 802.11 wireless networks that incorporates data-rate trends into the handoff decision process. The method continuously monitors historical and real-time network parameters, with particular emphasis on the user's current and predicted DR , to anticipate service degradation before it becomes critical. By predicting the future data-rate condition of the serving cell and comparing it with candidate neighbouring cells, the technique aims to identify an appropriate handoff opportunity proactively rather than waiting for conventional threshold-based degradation. The approach reduces unnecessary handoffs, minimize service interruption, and maintain a more stable and higher-quality DR during user mobility. Consequently, the study addresses a key gap in existing IEEE 802.11 handoff mechanisms by shifting the decision criterion from predominantly signal-strength-based handoff toward data-rate-aware predictive handoff, providing a basis for more reliable mobility management and improved Quality of Service (QoS) in dynamic wireless environments.

Keywords:

IEEE 802.11 wireless networks, Predictive Handoff, Inter-cell Handoff, Access point, Received signal strength, Mobility management, Data-rate-aware Handoff

References

  1. [1] Crow, B. P., Widjaja, I., Kim, J. G., & Sakai, P. T. (1997). IEEE 802.11 wireless local area networks. IEEE communications magazine, 35(9), 116–126. https://doi.org/10.1109/35.620533

  2. [2] Association., I. S. (2023). The evolution of Wi-Fi technology and standards. IEEE Standards Association. https://standards.ieee.org/beyond-standards/the-evolution-of-wi-fi-technology-and-standards/

  3. [3] Banerji, S., & Chowdhury, R. S. (2013). On IEEE 802.11: Wireless LAN technology. https://doi.org/10.48550/arXiv.1307.2661

  4. [4] Elkhodr, M., Shahrestani, S., & Cheung, H. (2016). Emerging wireless technologies in the internet of things: A comparative study. https://doi.org/10.48550/arXiv.1611.00861

  5. [5] Nedeltchev, P. (2001). Wireless local area networks and the 802.11 standard [White paper]. Cisco Systems. https://www.cs.mun.ca/~yzchen/bib/80211_whitepaper.pdf

  6. [6] Raghavendra, R., Belding, E. M., Papagiannaki, K., & Almeroth, K. C. (2007). Understanding handoffs in large IEEE 802.11 wireless networks. Proceedings of the 7th ACM SIGCOMM conference on internet measurement (pp. 333-338). Association for Computing Machinery (ACM). https://doi.org/10.1145/1298306.1298353

  7. [7] Usui, T. (2011). Designing improved traffic control in network-based seamless mobility management for wireless LAN. The third international conference on advances in future internet (AFIN) (pp. 96–101). IARIA. file:///C:/Users/Admin/Downloads/afin_2011_full (1).pdf

  8. [8] Bien, V. Q. (2014). Handoff management in radio over fiber 60 GHz indoor networks. https://doi.org/10.4233/uuid%3Ab913c0ee-fa19-44a6-a7ef-41fecde7125c

  9. [9] Sepúlveda, R., Montiel-Ross, O., Manzanarez, J. C., & Quiroz, E. E. (2012). Fuzzy logic predictive algorithm for wireless-LAN fast inter-cell handoff. Engineering letters, 20(1), 109–115. https://www.engineeringletters.com/issues_v20/issue_1/EL_20_1_14.pdf

  10. [10] Tetarwal, M. L., Kuntal, A., & Karmakar, P. (2014). A review on handoff latency reducing techniques in IEEE 802.11 WLAN. International journal of computer applications, NWNC, (2), 22–28. https://www.ijcaonline.org/proceedings/nwnc/number2/16118-1424/

  11. [11] Mishra, A., Shin, M., & Arbaugh, W. (2003). An empirical analysis of the IEEE 802.11 MAC layer handoff process. ACM sigcomm computer communication review, 33(2), 93–102. https://doi.org/10.1145/956981.956990

  12. [12] Kim, H. S., Park, S. H., Park, C. S., Kim, J. W., & Ko, S. J. (2004). Selective channel scanning for fast handoff in wireless LAN using neighbor graph. Proceedings of the 2004 international technical conference on circuits/systems, computers and communications (ITC-CSCC) (pp. 1–4). ITC-CSCC / IEEE-Related Conference Proceedings. https://dl.ifip.org/db/conf/ifip6-8/pwc2004/ParkKPKK04.pdf

  13. [13] Sanghavi, N., & Bansode, R. S. (2015). Improving IEEE 802.11 WLAN handoff latency by access point-based modification. Global journal of computer science and technology: E network, web & security, 15(5), 37–40. file:///C:/Users/Admin/Downloads/5-Improving-IEEE_pdf%20(1).pdf

  14. [14] Dolińska, I., Masiukiewicz, A., & Rządkowski, G. (2013). The mathematical model for interference simulation and optimization in 802.11n networks. Proceedings of the 22nd international workshop on concurrency, specification and programming (CS&P) (pp. 99–110). CEUR-WS.org. http://www.vistula.edu.pl

  15. [15] Seo, S., Song, J., Wu, H., & Zhang, Y. (2009). Achievable throughput-based MAC layer handoff in IEEE 802.11 wireless local area networks. EURASIP journal on wireless communications and networking, 2009. https://doi.org/10.1155/2009/467315

  16. [16] Shao, S., Zheng, J., Zhong, C., Lu, P., Guo, S., & Bu, X. (2023). IEEE 802.11ax meet edge computing: AP seamless handover for multi-service communications in industrial WLAN. IEEE transactions on network and service management, 20(3), 3396–3412. https://doi.org/10.1109/TNSM.2023.3239404

  17. [17] Sulaiman, T. H., & Al-Raweshidy, H. S. (2025). Predictive handover mechanism for seamless mobility in 5G and beyond networks. IET communications, 19(1), e12878. https://doi.org/10.1049/cmu2.12878

  18. [18] Khan, M. A., Hamila, R., Gastli, A., Kiranyaz, S., & Al-Emadi, N. A. (2022). ML-based handover prediction and AP selection in cognitive Wi-Fi networks. Journal of network and systems management, 30(4). https://doi.org/10.1007/s10922-022-09684-2

  19. [19] de Castro Monteiro, C., de Lira Gondim, P. R., de Miranda Rios, V., Coelho, A., & Martins, S. M. (2010). Video session handoff between WLANs. 2010 the 12th international conference on advanced communication technology (ICACT) (Vol. 2, pp. 1203-1208). IEEE. https://doi.org/10.1109/ISWCS.2009.5282300

  20. [20] Berezin, M. E., Rousseau, F., & Duda, A. (2011). Multichannel virtual access points for seamless handoffs in IEEE 802.11 wireless networks. 2011 IEEE 73rd vehicular technology conference (VTC Spring) (pp. 1-5). IEEE. https://doi.org/10.1109/VETECS.2011.5956552

  21. [21] Chan, Y. C., & Lin, D. J. (2014). The design of an AP-based handoff scheme for IEEE 802.11 WLANs. International journal of e-education, e-business, e-management and e-learning, 4(1), 72–76. https://doi.org/10.7763/IJEEEE.2014.V4.305

  22. [22] Christopher, A. F., & Jeyakumar, M. K. (2013). User data rate based vertical handoff in 4G wireless networks. Journal of theoretical and applied information technology, 58(1), 166–176. https://www.jatit.org/volumes/Vol58No1/18Vol58No1.pdf

Published

2025-12-12

How to Cite

Falana, O. T. ., Oluwadare, S. A. ., & Boyinbode, O. K. . (2025). Data Rate-Aware Predictive Inter-Cell Handoff Technique for IEEE 802.11 Wireless Networks. Information Sciences and Technological Innovations, 2(4), 303-315. https://doi.org/10.48314/isti.vi.57

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