Wireless Networks

, Volume 24, Issue 4, pp 1205–1215 | Cite as

Distributed throughput optimization for heterogeneous IEEE 802.11 DCF networks

  • Xinghua Sun
  • Yayu Gao


For IEEE 802.11 DCF networks in ad-hoc mode, how to achieve the maximum throughput in a distributed manner draws much attention in previous studies. The problem becomes challenging for partially-saturated heterogeneous networks with multiple groups, as the optimal access parameters not only depend on the group size of saturated groups but also the aggregate input rate of all the unsaturated groups, both of which are hard to obtain without a central controller. In this paper, a novel distributive scheme is proposed for partially-saturated heterogeneous IEEE 802.11 DCF networks to achieve the maximum network throughput. With the proposed scheme, each saturated transmitter can obtain the optimal initial backoff window size distributively by two estimation rounds. In each estimation round, each saturated transmitter only needs to count the number of busy intervals and ACK frames on the channel. For fully-saturated networks, only one estimation round is needed. It is shown by extensive simulations that the proposed scheme can achieve the maximum network throughput in a distributive manner.


Distributed throughput optimization Heterogeneous IEEE 802.11 DCF networks Partial saturation 



This work is supported in part by the National Natural Science Foundation of China (Grant Nos. 61401224 and 61402186), in part by the Natural Science Foundation of Jiangsu Province of China (Grant No. BK20140882), in part by NUPTSF (Grant No. NY213061) and in part by China Scholarship Council.


  1. 1.
    Gupta, A., Min, J., & Rhee, I. (2012). WiFox: Scaling WiFi Performance for Large Audience Environments. Proceedings of CoNEXT (pp. 217–228)Google Scholar
  2. 2.
    Bianchi, G. (2000). Performance analysis of the IEEE 802.11 distributed coordination function. IEEE J Sel Areas Commun, 18(3), 535–547.MathSciNetCrossRefGoogle Scholar
  3. 3.
    Bianchi, G., & Tinnirello, I. (2003). Kalman filter estimation of the number of competing terminals in an IEEE 802.11 network. Proceedings of IEEE INFOCOM (vol. 2, pp. 844–852), doi: 10.1109/INFCOM.2003.1208922
  4. 4.
    Toledo, A., Vercauteren, T., & Wang, X. (2006). Adaptive optimization of IEEE 802.11 DCF based on Bayesian estimation of the number of competing terminals. IEEE Trans Mob Comput, 5(9), 1283–1296. doi: 10.1109/TMC.2006.124.CrossRefGoogle Scholar
  5. 5.
    Cali, F., Conti, M., & Gregori, E. (2000). Dynamic tuning of the IEEE 802.11 protocol to achieve a theoretical throughput limit. IEEE/ACM Trans Netw, 8(6), 785–799.CrossRefGoogle Scholar
  6. 6.
    Dai, L., & Sun, X. (2013). A unified analysis of IEEE 802.11 DCF networks: Stability, throughput, and delay. IEEE Trans Mob Comput, 12(8), 1558–1572.CrossRefGoogle Scholar
  7. 7.
    Li, B., Battiti, R., & Fang, Y. (2007). Achieving optimal performance by using the IEEE 802.11 MAC protocol with service differentiation enhancements. IEEE Trans Veh Technol, 56(3), 1374–1387. doi: 10.1109/TVT.2007.895565.CrossRefGoogle Scholar
  8. 8.
    Freitag, J., & da Fonseca, N. L. S. (2006). Tuning of 802.11e network parameters. IEEE Commun Lett, 10(8), 611–613. doi: 10.1109/LCOMM.2006.1665127.CrossRefGoogle Scholar
  9. 9.
    Gao, Y., Sun, X., & Dai, L. (2014). IEEE 802.11e EDCA networks: Modeling, differentiation and optimization. IEEE Trans Wirel Commun, 13(7), 3863–3879.CrossRefGoogle Scholar
  10. 10.
    Heusse, M., Rousseau, F., Guillier, R., & Duda, A. (2005). Idle sense: An optimal access method for high throughput and fairness in rate diverse wireless LANs. SIGCOMM Comput Commun Rev, 35(4), 121–132.CrossRefGoogle Scholar
  11. 11.
    Cali, F., Conti, M., & Gregori, E. (2000b). IEEE 802.11 protocol: Design and performance evaluation of an adaptive backoff mechanism. IEEE J Sel Areas Commun, 18(9), 1774–1786. doi: 10.1109/49.872963.CrossRefGoogle Scholar
  12. 12.
    Ge, Y., Hou, J. C., & Choi, S. (2007). An analytic study of tuning systems parameters in IEEE 802.11e enhanced distributed channel access. Comput Netw, 51(8), 1955–1980.CrossRefzbMATHGoogle Scholar
  13. 13.
    Le, Y., Ma, L., Cheng, W., Cheng, X., & Chen, B. (2015). A time fairness-based MAC algorithm for throughput maximization in 802.11 networks. IEEE Trans Comput, 64(1), 19–31. doi: 10.1109/TC.2013.186.MathSciNetCrossRefGoogle Scholar
  14. 14.
    Mao, J., Mao, Y., Leng, S., & Bai, X. (2009). A simple adaptive optimization scheme for IEEE 802.11 with differentiated channel access. IEEE Commun Lett, 13(5), 297–299.CrossRefGoogle Scholar
  15. 15.
    Hu, C., & Hou, J.C. (2007). A Novel Approach to Contention Control in IEEE 802.11e-Operated WLANs. Proceedings of IEEE INFOCOM (pp. 1190–1198)Google Scholar
  16. 16.
    Gao, Y., Sun, X., & Dai, L. (2013). Throughput optimization of heterogeneous IEEE 802.11 DCF networks. IEEE Trans Wirel Commun, 12(1), 398–411. doi: 10.1109/TWC.2012.120312.120827.CrossRefGoogle Scholar
  17. 17.
    Ni, J., Tan, B., & Srikant, R. (2010). Q-CSMA: Queue-Length Based CSMA/CA Algorithms for Achieving Maximum Throughput and Low Delay in Wireless Networks. Proceedings of INFOCOM (pp. 1–5)Google Scholar
  18. 18.
    Jiang, L., & Walrand, J. (2011). Approaching throughput-optimality in distributed CSMA scheduling algorithms with collisions. IEEE/ACM Trans Netw, 19(3), 816–829.CrossRefGoogle Scholar
  19. 19.
    Wu, D., Bao, L., Regan, A. C., & Talcott, C. L. (2013). Large-scale access scheduling in wireless mesh networks using social centrality. J Parallel Distrib Comput, 73(8), 1049–1065.CrossRefzbMATHGoogle Scholar
  20. 20.
    Wu, D., Bao, L., & Liu, C. H. (2013). Scalable channel allocation and access scheduling for wireless internet-of-things. IEEE Sens J, 13(10), 3596–3604.CrossRefGoogle Scholar
  21. 21.
    Corless, R., Gonnet, G., Hare, D., Jeffrey, D., & Knuth, D. (1996). On the LambertW function. Adv Comput Math, 5(1), 329–359.MathSciNetCrossRefzbMATHGoogle Scholar
  22. 22.
    IEEE 802.11n-2009. (2009). Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 5: Enhancements for Higher Throughput.Google Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Jiangsu Key Lab of Wireless Communications, Key Lab on Wideband Wireless Communications and Sensor Network Technology of Ministry of EducationNanjing University of Posts and TelecommunicationsNanjingChina
  2. 2.School of Electronic Information and Communications Huazhong University of Science and TechnologyWuhanChina

Personalised recommendations