Global Optimal Routing, Scheduling and Power Control for Multi-Hop Wireless Networks with Interference

  • Seyed Javad KazemitabarEmail author
Part of the Signals and Communication Technology book series (SCT)


It happens often that the physical layer algorithm in use is not capable of removing the interference. It then will be with the MAC layer on how to optimize the transmission in order to use less resources of the network, e.g. power. In this chapter we assume full interference from all links in the network with their corresponding weight. After approximating the capacity formula, we then introduce an efficient joint routing, scheduling and power control algorithm that minimizes the consumes power while providing the end-to-end data flow.


Extreme Point Power Control Optimal Route Traffic Demand Rate Vector 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 36.
    R. Cruz, A. Sanathanam, Optimal routing, link scheduling and power control in multi-hop wireless networks, in Proc. IEEE INFOCOM, 2003 Google Scholar
  2. 37.
    A. Sanathanam, Joint optimization of radio resources in wireless multi-hop networks. Ph.D. thesis, University of California, San Diego Google Scholar
  3. 40.
    L. Lin, X. Lin, N. Shroff, Low-complexity and distributed energy minimization in multi-hop wireless networks, in Proc. INFOCOM 2007, 2007 Google Scholar
  4. 41.
    M.J. Neely, Energy optimal control for time varying wireless networks. IEEE Trans. Inf. Theory 52(2), 2915–2934 (2006) MathSciNetCrossRefGoogle Scholar
  5. 45.
    J. Kazemitabar, H. Yousefi’zadeh, H. Jafarkhani, Impact of physical layer parameters on connectivity of ad hoc networks, in Proc. IEEE ICC, 2006 Google Scholar
  6. 46.
    H. Jafarkhani, H. Yousefi’zadeh, J. Kazemitabar, Capacity-based connectivity of MIMO fading ad hoc networks, in Proc. IEEE Globecom, 2005 Google Scholar
  7. 47.
    H. Yousefi’zadeh, H. Jafarkhani, J. Kazemitabar, Outage probability metrics of connectivity for MIMO fading ad-hoc networks, in Proc. IEEE Milcom, 2005 Google Scholar
  8. 48.
    H. Yousefi’zadeh, H. Jafarkhani, J. Kazemitabar, A study of connectivity in MIMO fading ad-hoc networks. J. Commun. Netw. 11(1), 47–56 (2009) Google Scholar
  9. 49.
    J.E. Kelly Jr., The cutting plane method for solving convex programs. J. Soc. Ind. Appl. Math. 8(4), 418–429 (1960) Google Scholar
  10. 50. Accessed 10 Oct. 2010
  11. 51.
  12. 52.
    S. Boyd, L. Vanderberghe, Convex Optimization (Cambridge University Press, Cambridge, 2004) zbMATHGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Dept. of EE and CSUniversity of California IrvineIrvineUSA

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