• DocumentCode
    178809
  • Title

    Green resource allocation in relay-assisted MIMO systems with statistical channel state information

  • Author

    Zappone, Alessio ; Pan Cao ; Jorswieck, Eduard

  • Author_Institution
    Commun. Lab., Tech. Univ. Dresden, Dresden, Germany
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    3508
  • Lastpage
    3512
  • Abstract
    Green resource allocation in an amplify-and-forward (AF) relay-assisted MIMO system is considered, consisting of one source, one AF relay, and one destination, in which the relay-to-destination channel is only statistically known to the source and relay. The source covariance matrix and the relay AF matrix are optimized so as to maximize the system energy efficiency (EE), defined as the ratio of the system ergodic achievable rate over the total consumed power. The resulting optimization problem is a challenging non-convex problem, which is tackled employing fractional programming in conjunction with the alternating maximization algorithm. In addition, the regime of single-stream transmission is investigated and a sufficient condition for its optimality is derived.
  • Keywords
    MIMO communication; amplify and forward communication; concave programming; covariance matrices; relay networks (telecommunication); statistical analysis; wireless channels; EE; amplify-and-forward relay-assisted MIMO system; energy efficiency; fractional programming; green resource allocation; maximization algorithm; relay AF matrix; relay-to-destination channel; single-stream transmission; source covariance matrix; statistical channel state information; MIMO; Optimization; Power control; Programming; Relays; Resource management; Wireless communication; Energy Efficiency; Fractional programming; Multiple-antenna systems; Relay-Assisted communications; Statistical CSI;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6854253
  • Filename
    6854253