Sensing-throughput optimization for cognitive radio networks under outage constraints and hard decision fusion Conference Paper uri icon

abstract

  • The trade-off problem between spectrum sensing time and cognitive user%27s maximum achievable throughput is addressed here for a hard-decision-fusion-based cooperative cognitive radio network. Spectrum sensing is carried out using the energy detector. In the literature, fusion rules have been investigated and compared in terms of secondary user%27s throughput performance by assuming that the primary signal-to-noise ratios (SNRs) at the secondary (or cognitive) users%27 receivers are all equal. Here, we include small-scale (Nakagami-m) fading in the channel model which leads to different and random instantaneous SNRs at the cognitive radios. An outage constraint on the global probability of detection is used as a design approach to optimize the number of symbols used for periodic spectrum sensing. Simulation results show that the Majority rule attains the maximum achievable throughput. © 2015 IEEE.
  • The trade-off problem between spectrum sensing time and cognitive user's maximum achievable throughput is addressed here for a hard-decision-fusion-based cooperative cognitive radio network. Spectrum sensing is carried out using the energy detector. In the literature, fusion rules have been investigated and compared in terms of secondary user's throughput performance by assuming that the primary signal-to-noise ratios (SNRs) at the secondary (or cognitive) users' receivers are all equal. Here, we include small-scale (Nakagami-m) fading in the channel model which leads to different and random instantaneous SNRs at the cognitive radios. An outage constraint on the global probability of detection is used as a design approach to optimize the number of symbols used for periodic spectrum sensing. Simulation results show that the Majority rule attains the maximum achievable throughput. © 2015 IEEE.

publication date

  • 2015-01-01