Sensing-throughput optimization for cognitive radio networks under outage constraints and hard decision fusion

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.