• DocumentCode
    265847
  • Title

    Effective capacity in cognitive radio broadcast channels

  • Author

    Hammouda, Marwan ; Akin, Sami ; Peissig, Jurgen

  • Author_Institution
    Inst. of Commun. Technol., Leibniz Univ. Hannover, Hannover, Germany
  • fYear
    2014
  • fDate
    8-12 Dec. 2014
  • Firstpage
    1071
  • Lastpage
    1077
  • Abstract
    In this paper, we investigate effective capacity by modeling a cognitive radio broadcast channel with one secondary transmitter (ST) and two secondary receivers (SRs) under quality-of-service constraints and interference power limitations. We initially describe three different cooperative channel sensing strategies with different hard-decision combining algorithms at the ST, namely OR, Majority, and AND rules. Since the channel sensing occurs with possible errors, we consider a combined interference power constraint by which the transmission power of the secondary users (SUs) is bounded when the channel is sensed as both busy and idle. Furthermore, regarding the channel sensing decision and its correctness, there exist possibly four different transmission scenarios. We provide the instantaneous ergodic capacities of the channel between the ST and each SR in all of these scenarios. Granting that transmission outage arises when the instantaneous transmission rate is greater than the instantaneous ergodic capacity, we establish two different transmission rate policies for the SUs when the channel is sensed as idle. One of these policies features a greedy approach disregarding a possible transmission outage, and the other favors a precautious manner to prevent this outage. Subsequently, we determine the effective capacity region of this channel model, and we attain the power allocation policies that maximize this region. Finally, we present the numerical results. We first show the superiority of Majority rule when the channel sensing results are good. Then, we illustrate that a greedy transmission rate approach is more beneficial for the SUs under strict interference power constraints, whereas sending with lower rates will be more advantageous under loose interference constraints. Finally, we note that the methodology and the approach we consider in this study can be easily applied into a more general cognitive radio broadcast channel model with more than two SRs.
  • Keywords
    broadcast channels; channel capacity; cognitive radio; cooperative communication; signal detection; cognitive radio broadcast channel; cooperative channel sensing; effective channel capacity; hard decision combining algorithm; interference power limitations; majority rule; quality of service constraints; secondary receiver; secondary transmitter; transmission outage; Cognitive radio; Fading; Interference; Quality of service; Radio transmitters; Receivers; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Communications Conference (GLOBECOM), 2014 IEEE
  • Conference_Location
    Austin, TX
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2014.7036951
  • Filename
    7036951