Chinese Journal of Quantum Electronics, Volume. 33, Issue 6, 757(2016)

Distributed cross layer joint resource allocation algorithm based on compensation CSI

Jun ZHANG1,2、* and Wenjie LIU2
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
  • show less

    In order to eliminate the effect of outdated channel state information(CSI) on cross layer resource allocation efficiency in distributed wireless multi-hop network environment, and improve the accuracy of cross layer joint resource allocation, a compensation cross layer joint resource allocation algorithm based on channel correlation is proposed. The conditional probability density function between the instantaneous and outdated channel state information is adopted, and the closed solution of the conditional capacity under the condition of signal to interference plus Noise Ratio(SINR) is obtained based on Rayleigh fading channel model. In order to compensate for the partial network performance loss, a joint congestion control, channel allocation and power control algorithm considering the outdated state information is proposed. In the process the network is modeled as a Networkunility Maximization (NUM) problem, and the variable link data rate and power resource constraints are used as constraints. By using Lagrange dual decomposition technique, the NUM problem is solved by distributed solution. Experimental comparison analysis show that under the promise of ensuring lower complexity, the algorithm can effectively improve the reasonable allocation of resources in distributed multi-hop network, so that the overall utility of the network is improved, and the energy consumption is reduced.

    Tools

    Get Citation

    Copy Citation Text

    ZHANG Jun, LIU Wenjie. Distributed cross layer joint resource allocation algorithm based on compensation CSI[J]. Chinese Journal of Quantum Electronics, 2016, 33(6): 757

    Download Citation

    EndNote(RIS)BibTexPlain Text
    Save article for my favorites
    Paper Information

    Category:

    Received: Sep. 21, 2015

    Accepted: --

    Published Online: Jan. 3, 2017

    The Author Email: Jun ZHANG (zhangjun-zju@163.com)

    DOI:10.3969/j.issn.1007-5461. 2016.06.017

    Topics