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Bandwidth-Efficient Joint User-Association and Resource-Allocation in Multi-Cell VWN

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Virtualized Wireless Networks

Part of the book series: SpringerBriefs in Electrical and Computer Engineering ((BRIEFSELECTRIC))

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Abstract

This chapter addresses the user association and resource allocation problem in a multi-cell VWN where users belong to different slices with each slice requiring a minimum reserved rate from the network. We formulate a bandwidth-efficient joint user-association and resource-allocation scheme that assigns users to BS and allocates the sub-carriers and power to maximize the total achieved sum-rate of the network subject to the rate reservation per slices.

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Notes

  1. 1.

    CVX chooses its own initialize value for vector \(\boldsymbol{\alpha }\) [13], which is applied for our algorithm to check the convergence condition.

References

  1. R. Kokku, R. Mahindra, H. Zhang, and S. Rangarajan, “NVS: A substrate for virtualizing wireless resources in cellular networks,” IEEE/ACM Trans. Netw., vol. 20, no. 5, Oct. 2012.

    Google Scholar 

  2. C. Liang and F. Yu, “Wireless network virtualization: A survey, some research issues and challenges,” IEEE Commun. Surveys Tuts., vol. 17, no. 99, pp. 358–380, Aug. 2014.

    Google Scholar 

  3. F. Fu and U. Kozat, “Stochastic game for wireless network virtualization,” IEEE/ACM Trans. Netw., vol. 21, no. 1, pp. 84–97, Feb. 2013.

    Google Scholar 

  4. S. Parsaeefard, V. Jumba, M. Derakhshani, and T. Le-Ngoc, “Joint resource provisioning and admission control in wireless virtualized networks,” in IEEE Wireless Commun. Netw. Conf. (WCNC), Mar. 2015, pp. 2020–2025.

    Google Scholar 

  5. V. Jumba, S. Parsaeefard, M. Derakhshani, and T. Le-Ngoc, “Resource provisioning in wireless virtualized networks via massive-MIMO,” IEEE Wireless Commun. Lett., vol. 4, no. 3, pp. 237–240, Feb. 2015.

    Google Scholar 

  6. X. Zhang, Y. Li, D. Jin, L. Su, L. Zeng, and P. Hui, “Efficient resource allocation for wireless virtualization using time-space division,” in IEEE Intl. Conf. on Wireless Commun. and Mobile Comp. (IWCMC), Aug. 2012, pp. 59–64.

    Google Scholar 

  7. G. Liu, F. Yu, H. Ji, and V. Leung, “Distributed resource allocation in full-duplex relaying networks with wireless virtualization,” in IEEE Global Commun. Conf. (GLOBECOM), Dec. 2014, pp. 4959–4964.

    Google Scholar 

  8. Z.-Q. Luo and S. Zhang, “Dynamic spectrum management: Complexity and duality,” IEEE J. Sel. Topics in Signal Processing, vol. 2, no. 1, pp. 57–73, Feb. 2008.

    Google Scholar 

  9. M. Chiang, “Geometric programming for communication systems,” Foundations and Trends in Communications and Information Theory, vol. 2, no. 1–2, pp. 1–154, 2005.

    Article  MATH  Google Scholar 

  10. M. Chiang, C. W. Tan, D. Palomar, D. O’Neill, and D. Julian, “Power control by geometric programming,” IEEE Trans. Wireless Commun., vol. 6, no. 7, pp. 2640–2651, July 2007.

    Google Scholar 

  11. G. Xu, “Global optimization of signomial geometric programming problems,” European Journal of Operational Research, vol. 233, no. 3, pp. 500–510, 2014.

    Article  MathSciNet  MATH  Google Scholar 

  12. M. Derakhshani, X. Wang, T. Le-Ngoc, and A. Leon-Garcia, “Airtime usage control in virtualized multi-cell 802.11 networks,” in IEEE Global Commun. Conf. (GLOBECOM), Dec. 2015, pp. 1–6.

    Google Scholar 

  13. M. Grant and S. Boyd, “CVX: Matlab software for disciplined convex programming, version 2.1,” http://cvxr.com/cvx, 2014.

  14. S. Boyd and L. Vandenberghe, Convex Optimization. Cambridge University Press, 2009.

    MATH  Google Scholar 

  15. M. Avriel and A. Williams, “Complementary geometric programming,” SIAM Journal on Applied Mathematics, vol. 19, no. 1, pp. 125–141, 1970.

    Article  MathSciNet  MATH  Google Scholar 

  16. B. Marks and G. Wright, “A general inner approximation algorithm for nonconvex mathematical programs,” Journal of Operations Research, vol. 26, no. 8, pp. 681–683, 1978.

    Article  MathSciNet  MATH  Google Scholar 

  17. A. Goldsmith, Wireless Comunications. Cambridge University Press, 2004.

    Google Scholar 

  18. M. Razaviyayn, “Successive convex approximation: Analysis and Applications,” in IEEE Wireless Commun. Netw. Conf. (WCNC), May 2014.

    Google Scholar 

  19. D. T. Ngo, S. Khakurel, and T. Le-Ngoc, “Joint subchannel assignment and power allocation for OFDMA femtocell networks,” IEEE Trans. Wireless Commun., vol. 13, no. 1, pp. 342–355, Jan. 2014.

    Google Scholar 

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Le-Ngoc, T., Dawadi, R., Parsaeefard, S., Derakhshani, M. (2018). Bandwidth-Efficient Joint User-Association and Resource-Allocation in Multi-Cell VWN. In: Virtualized Wireless Networks. SpringerBriefs in Electrical and Computer Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-57388-5_2

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  • DOI: https://doi.org/10.1007/978-3-319-57388-5_2

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