  The concept of cognitive radio pioneered by Mitola promises to change the
future of wireless communication especially in the area of spectrum management.
Currently, the command and control strategy employed in spectrum assignment is
too rigid and needs to be reviewed. Recent studies have shown that assigned
spectrum is underutilized spectrally and temporally. Cognitive radio provides a
viable solution whereby licensed users can share the spectrum with unlicensed
users opportunistically without causing interference. Unlicensed users must be
able to sense weather the channel is busy or idle, failure to do so will lead
to interference to the licensed user. In this paper, a neural network based
prediction model for predicting the channel status using historical data
obtained during a spectrum occupancy measurement is presented. Genetic
algorithm is combined with LM BP for increasing the probability of obtaining
the best weights thus optimizing the network. The results obtained indicate
high prediction accuracy over all bands considered
