Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Iterative power control based admission control for wireless networks

  • 228 Accesses

  • 4 Citations


This paper studies transmission power control algorithms for cellular networks. One of the challenges in commonly used iterative mechanisms to achieve this is to identify if the iteration will converge since convergence indicates feasibility of transmit power allocation under prevailing network conditions. The convergence criterion should also be simple to calculate given the time constraints in a real-time wireless network. Towards this goal, this paper derives simple sufficient conditions for convergence of an iterative power control algorithm using existing bounds from matrix theory. With the help of suitable numerical examples, it is shown that the allocated transmit powers of the nodes converge when sufficient conditions are satisfied, and diverge when they are not satisfied. This forms the basis for an efficient link data-rate based admission control mechanism for wireless networks. The mechanism considers parameters such as signal strength requirement, link datarate requirement, and number of nodes in the system. Simulation based analysis shows that existing links are able to maintain their desired datarates despite the addition of new wireless links.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8


  1. 1.

    Anas, M., Rosa, C., Calabrese, F., Michaelsen, P., Pedersen, K., & Mogensen, P. (2008). QoS-aware single cell admission control for UTRAN LTE uplink. In IEEE vehicular technology conference, Singapore (pp. 2487–2491).

  2. 2.

    Andersin, M., Rosberg, Z., Zander, J., Andersin, M., Rosberg, Z., & Zanders, J. (1997). Soft and safe admission control in cellular networks. IEEE/ACM Transactions on Networking, 5, 255–265.

  3. 3.

    Cohen, J. E., & Newman, C. M. (1984). The stability of large random matrices and their products. The Annals of Probability, 12, 283–310.

  4. 4.

    Collotta, M., Pau, G., & Scata, G. (2014). A fuzzy system to reduce power consumption in wireless sensor networks: A comparison between WirelessHART and IEEE 802.15.4. In IEEE international energy conference (ENERGYCON).

  5. 5.

    Dembo, A. (1988). Bounds on the extreme eigenvalues of positive-definite Toeplitz matrices. IEEE Transactions on Information Theory, 34, 352–355.

  6. 6.

    Douros, V. G., & Polyzos, G. C. (2011). Review of some fundamental approaches for power control in wireless networks. Computer Communications, 34, 1580–1592.

  7. 7.

    Foschini, G., & Miljanic, Z. (1993). A simple distributed autonomous power control algorithm and its convergence. IEEE Transactions on Vehicular Technology, 42(4), 641–646.

  8. 8.

    Garren, K. R. (1968). Bounds for the eigenvalues of a matrix. NASA Technical Note, NASA TND-4373 (196).

  9. 9.

    Glasserman, P., & Yao, D. D. (1995). Stochastic vector difference equations with stationary coefficients. Journal of Applied Probability, 32, 851–866.

  10. 10.

    Grandhi, S. A., & Zanders, J. (1994). Constrained power control in cellular radio systems. In IEEE vehicular technology conference (pp. 824–828).

  11. 11.

    Hande, P., Rangan, S., Chiang, M., & Wu, X. (2008). Distributed uplink power control for optimal SIR assignment in cellular data networks. IEEE/ACM Transactions on Networking, 16, 1420–1433.

  12. 12.

    Hande, P., Rangan, S., Chiang, M., & Wu, X. (2008). Distributed uplink power control for optimal SIR assignment in cellular data networks. IEEE/ACM Transactions on Networking, 16(6), 1420–1433.

  13. 13.

    Han, Z., & Liu, K. J. R. (2008). Resource allocation for wireless networks: Basics, techniques, and applications. Cambridge: Cambridge University Press.

  14. 14.

    James, G., & Rumchev, V. (2005). Stability of positive linear discrete-time systems. Bulletin of the Polish Academy of Sciences Technical Sciences, 53, 1–8.

  15. 15.

    Karthik, R. M., Narendran, K., & Sivalingam, K. M. (2011). Convergence conditions for iterative transmission power control algorithms in wireless networks. In IEEE Advanced Networks and Telecommunication Systems (ANTS).

  16. 16.

    Kawadia, V., & Kumar, P. R. (2005). Principles and protocols for power control in wireless ad hoc networks. IEEE Journal on Selected Areas in Communications, 23, 76–88.

  17. 17.

    Kou, Ke-hao, Tang, Bi-hua, Liu, Kai-ming, & Ma, Tao. (2013). Capacity analysis of based-regular-topologies cognitive wireless mesh networks with power control. The Journal of China Universities of Posts and Telecommunications, 20, 71–78.

  18. 18.

    Lee, J., & Chung, K. (2011). An efficient transmission power control scheme for temperature variation in wireless sensor networks. Sensors, 11, 3078–3093.

  19. 19.

    Liu, Z., & Zarki, M. E. (1994). SIR-based call admission control for DS-CDMA cellular systems. IEEE Journal on Selected Areas in Communications, 12, 638–644.

  20. 20.

    Messier, G. G., Hartwell, J. A., & Davies, R. J. (2008). A sensor network cross-layer power control algorithm that incorporates multiple-access interference. IEEE Transactions on Wireless Communications, 7, 2877–2883.

  21. 21.

    Minc, H. (1988). Nonnegative matrices. New York: Wiley.

  22. 22.

    Narendran, K. (2014). Interference management techniques: Power control and link adaptation. MS thesis, Indian Institute of Technology, Madras.

  23. 23.

    Narendran, K., Karthik, R. M., & Sivalingam, K. M. (2012). Link datarate based admission control in wireless networks. In IEEE Advanced Networks and Telecommunication Systems (ANTS)

  24. 24.

    Nie, N., Comaniciu, C., & Agrawal, P. (2007). A game theoretic approach to interference management in cognitive networks. Springer Wireless Communications, 143, 199–219.

  25. 25.

    Ostrowski, A., & Schneider, H. (1961). Bounds for the maximal characteristic root of a non-negative irreducible matrix. Duke Mathematical Journal, 27, 547–553.

  26. 26.

    Qin, C., Yu, G., Zhang, Z., Jia, H., & Huang, A. (2007). Power reservation-based admission control scheme for IEEE 802.16e OFDMA systems. In IEEE wireless communications and networking conference, Hong Kong (pp. 1831–1835).

  27. 27.

    Saraydar, C. U., Mandayam, N. B., & Goodman, D. (2002). Efficient power control via pricing in wireless data networks. IEEE Transactions on Communications, 50, 291–303.

  28. 28.

    Shannon, C. E., & Weaver, W. (1962). The mathematical theory of communication. Champaign: University of Illinois Press.

  29. 29.

    Varga, R. S. (2000). Matrix iterative analysis. Heidelberg: Springer.

  30. 30.

    Xiao, M., Shroff, N. B., & Chong, E. K. P. (2003). A utility-based power-control scheme in wireless cellular systems. IEEE/ACM Transactions on Networking, 11, 210–221.

  31. 31.

    Yates, R. D. (1995). A framework for uplink power control in cellular radio systems. IEEE Journal on Selected Areas in Communications, 13, 1341–1348.

  32. 32.

    Zander, J. (1992). Distributed cochannel interference control in cellular radio systems. IEEE Transactions on Vehicular Technology, 41, 305–311.

Download references


Parts of this paper were presented at IEEE ANTS 2011 Conference (Bangalore, India) and IEEE ANTS 2012 Conference (Bangalore, India). Part of this work was supported by India-UK Advanced Technology Centre of Excellence in Next Generation Networks, Systems and Services (IU-ATC).

Author information

Correspondence to K. Narendran.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Narendran, K., Karthik, R.M. & Sivalingam, K.M. Iterative power control based admission control for wireless networks. Wireless Netw 22, 619–633 (2016). https://doi.org/10.1007/s11276-015-0985-1

Download citation


  • Power control
  • Admission control
  • Iterative algorithm
  • Convergence of iterative algorithm
  • Wireless networks