Fractional sequential sensing for energy efficient cooperative cognitive radio networks

In this paper, we propose fractional sequential sensing (FSS) as a novel cooperative sensing scheme for cognitive radio networks. FSS compromises a tradeoff between sensing accuracy and efficiency by formulating an optimization problem whose solution identifies FSS sensing parameters. These parameters include the sensing period and channels allocated for each user. Our simulation results show that FSS successfully improves the sensing accuracy while maintaining a low power profile. Additionally, we show that the sensing accuracy performance gap between FSS and other traditional schemes increases by optimizing decision engine.