Cooperative spectrum sensing has been proposed
as a solution to increase the sensing function accuracy in cognitive
radio networks, but the research has, so far, mainly
focused on static scenarios, all but neglecting the impact of
mobility on spectrum sensing. In this work a novel cooperative
spectrum sensing scheme for mobile cognitive networks,
based on a correlation-based, mobility-aware node selection
algorithm is proposed. Correlation among sensing decisions
is used to divide nodes into groups, and mobility is taken into
account in the group leaders selection by means of a node
selection metric that considers both sensing performance and
mobility. Performance of the proposed algorithm is evaluated
by computer simulations taking into account mobility and
a detailed modeling of temporal and spatial correlation of fading
and shadowing components in the channel path loss, going
way beyond the performance evaluation carried out in previous
works on correlation-based cooperative sensing schemes.
Simulation results highlight that the proposed metric leads to
a signicant increase of the update period required to maintain
acceptable sensing performance, and correspondingly to
a strong reduction in the overhead caused by the grouping and
node selection procedure.
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