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Resource allocation algorithm for LTE networks using fuzzy based adaptive priority and effective bandwidth estimation

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Abstract

In this paper, we propose a scheme to allocate resource blocks for the Long Term Evolution (LTE) downlink based on the estimation of the effective bandwidths of traffic flows, where users’ priorities are adaptively computed using fuzzy logic. The effective bandwidth of each user traffic flow that is estimated through the parameters of the adaptive β-Multifractal Wavelet Mode modeling, is used to attain their quality of service (QoS) parameters. The proposed allocation scheme aims to guarantee the QoS parameters of users respecting the constraints of modulation and code schemes (modulation and coding scheme) of the LTE downlink transmission. The proposed algorithm considers the average channel quality and the adaptive estimation of effective bandwidth to decide about the scheduling of available radio resources. The efficiency of the proposed scheme is verified through simulations and compared to other algorithms in the literature in terms of parameters such as: system throughput, required data rate not provided, fairness index, data loss rate and network delay.

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Notes

  1. TCP/IP traffic between the University of Waykato and the rest of the world, collected from 07/04/2011 to 05/11/2011. The traffic traces can be found in http://wand.net.nz/wits/waikato/8/.

  2. Download traffic collected in 21/10/2015 from an internet computer.

References

  1. 3GPP TSG RAN TR 25.913 v8.0.0. (2008). Requirement for evolved Universal Terrestrial Radio Access (UTRA) and Universal Terrestrial Radio Access Network (UTRAN).

  2. Guan, N., Zhou, Y., Tian, L., Sun, G., & Shi, J. (2011). QoS guaranteed resource block allocation algorithm for LTE systems. In IEEE 7th international conference on wireless and mobile computing, networking and communications.

  3. Gonçalves, B. H. P., Vieira, F. H. T., & Costa, V. H. T. (2013). Modelagem Multifractal BetaMWM Adaptativa para Tráfego de Redes de Computadores. In X Encontro Anual de Computação.

  4. Su, L., & Ping Wang, F. L. (2012). Particle swarm optimization based resource block allocation algorithm for downlink LTE systems. In The 18th Asia-Pacific conference on communications.

  5. Dahlman, E., Parkvall, S., Sköld, J., & Beming, P. (2007). 3G evolution HSPA and LTE for mobile broadband. Oxford: Elsevier.

    Google Scholar 

  6. 3GPP TS 36.300 version 11.3.0 Release 110. (2012). LTE; Evolved Universal Terrestrial Radio Access (E-UTRA) and Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Overall description; Stage 2, November 2012.

  7. Shreedhar, M., & Varghese, G. (1996). Efficient fair queuing using deficit round-robin. IEEE/ACM Transactions on Networking, 4(3), 375–385.

    Article  Google Scholar 

  8. Jalali, A., Padovani, R., & Pankaj, R. (2000). Data throughput of CDMA-HDR a high efficiency-high data rate personal communication wireless system. In Vehicular technology conference (pp. 1854–1858).

  9. Shakkottai, S., & Stolyar, A. L. (2002). Scheduling for multiple flows sharing a time-varying channel: Exponential rule. In Yu. M. Suhov (Ed.), Analytic methods in applied probability (pp. 185–202). Providence, RI: American Mathematical Society.

    Google Scholar 

  10. Sadiq, B., Baek, S. J., & De Veciana, G. (2010). Delay-optimal opportunistic scheduling and approximations: The log rule. IEEE/ACM Transactions on Networking, 19(2), 405–418.

    Article  Google Scholar 

  11. Zolfaghari, A., & Taheri, H. (2015). Queue-aware channel-adapted scheduling and congestion control for best-effort services in LTE networks. Canadian Journal of Electrical and Computer Engineering, 38(2), 170–182.

    Article  Google Scholar 

  12. Liu, Y., Huynh, M., & Ghosal, D. (2016). Enhanced DRX-aware scheduling for mobile users in LTE networks. In 2016 international conference on computing, networking and communications (pp. 1–5). 15–18 February 2016.

  13. Chung, W.-C., Chang, C.-J., & Wang, L.-C. (2012). An intelligent priority resource allocation scheme for LTE—A downlink systems. IEEE Wireless Communications Letters, 1(3), 241–244.

    Article  Google Scholar 

  14. Khan, N., Martini, M. G., & Staehle, D. (2013). Opportunistic QoS-aware fair downlink scheduling for delay sensitive applications using fuzzy reactive and proactive controllers. In 2013 IEEE 78th vehicular technology conference (VTC Fall) (pp. 1–6). September 2–5, 2013.

  15. Wang, J., & Yin, Z. (2008). A ranking selection-based particle swarm optimizer for engineering design optimization problems. Structural and Multidisciplinary Optimization, 37, 131–147.

    Article  Google Scholar 

  16. Jang, J.-S. R., Sun, C.-T., & Mizutani, E. (1997). Neuro-fuzzy and soft computing: A computational approach to learning and machine intelligence. Upper Saddle River, NJ: Prentice-Hall.

    Google Scholar 

  17. Sugeno, M., & Kang, G. (1988). Structure identification of fuzzy model. Fuzzy Sets and Systems, 28(1), 15–33.

    Article  MathSciNet  MATH  Google Scholar 

  18. Takagi, T., & Sugeno, M. (1985). Fuzzy identification of systems and its applications to modeling and control. IEEE Systems, Man, and Cybernetics Society, 15(1), 116–132.

    Article  MATH  Google Scholar 

  19. Lee, C. C. (1990). Fuzzy logic in control systems: Fuzzy logic controller, part II. IEEE Transactions on Systems, Man, and Cybernetics, 20(2), 419–435.

    Article  MATH  Google Scholar 

  20. Kawser, M. T., Hamid, N. I. B., Hasan, M. N., Alam, M. S., & Rahman, M. (2012). Downlink SNR to CQI mapping for different multiple antenna techniques in LTE. International Journal of Information and Electronics Engineering, 2, 757.

    Google Scholar 

  21. Fisher, A., Calvet, L., & Mandelbrot, B. B. (1997). Multifractality of Deutschmark/US dollar exchanges rates. In Cowles Foundation discussion paper. New Haven: Yale University.

  22. Riedi, R. H., Crouse, M. S., Ribeiro, V. J., & Baraniuk, R. G. (1999). A multifractal wavelet model with application to network traffic. IEEE Transactions on Information Theory, 45(3), 992–1018.

    Article  MathSciNet  MATH  Google Scholar 

  23. Chui, C. K. (1992). An introduction to wavelets. San Diego: Academic Press.

    MATH  Google Scholar 

  24. Rocha, F. G. C., & Vieira, F. H. T. (2009). Modelagem de tráfego de vídeo MPEG-4 utilizando cascata multifractal com distribuição autorregressiva dos multiplicadores. In I2TS.

  25. Kelly, F. (1996). Notes on effective bandwidths. In F. P. Kelly (Ed.), Stochastic networks: Theory and applications (pp. 141–168). New York: Oxford University Press.

  26. Vieira, F. H. T., Bianchi, G. R., Ling, L. L., & Lemos, R. P. (2004). Estimação de banda efetiva dinâmica em redes de computadores utilizando uma modelagem auto-regressiva nebulosa. In XXI Simpósio Brasileiro de Telecomunicações (SBrT).

  27. Gonçalves, B. H. P., Vieira, F. H. T., & Costa, V. H. T. (2013). Alocação Dinâmica de Slots de Tempo Multiusuário para Redes OFDM/TDMA baseado em Banda Efetiva e Modelagem BMWM. In XXXI Simpósio Brasileiro de Telecomunicações - SBrT2013, Setembro 2013.

  28. Gibbens, R. J. (1996). Traffic characterization and effective bandwidths for broadband network traces. In S. Zachary & I. Ziedins (Eds.), Stochastic networks: Theory and application (Vol. 4, pp. 169–179). New York: Oxford University Press.

    Google Scholar 

  29. 3GPP TR 36.942 version10.2.0. (2011). LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Radio frequency (RF) system scenarios, May 2011.

  30. Ni, M., Xu, X., & Mathar, R. (2013). A channel feedback model with robust SINR prediction for LTE systems. In 7th European conference on antennas and propagation (EuCAP).

  31. Jain, R., Durresi, A., & Babic, G. (1999). Throughput fairness index: An explanation. Department of CIS, The Ohio State University, ATM_Forum/99-0045.

  32. 3GPP TS 36.104 version 10.2.0 Release 10. (2011). LTE; Evolved Universal Terrestrial Radio Access (E-UTRA); Base Station (BS) Radio Transmission and Reception.

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Correspondence to Diego Cruz Abrahão.

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Abrahão, D.C., Vieira, F.H.T. Resource allocation algorithm for LTE networks using fuzzy based adaptive priority and effective bandwidth estimation. Wireless Netw 24, 423–437 (2018). https://doi.org/10.1007/s11276-016-1344-6

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