  In Cognitive Radio Network (CRN), the secondary user (SU) opportunistically
access the wireless channels whenever they are free from the licensed / Primary
User (PU). Even after occupying the channel, the SU has to sense the channel
intermittently to detect reappearance of PU, so that it can stop its
transmission and avoid interference to PU. Frequent channel sensing results in
the degradation of SU's throughput whereas sparse sensing increases the
interference experienced by the PU. Thus, optimal sensing interval policy plays
a vital role in CRN. In the literature, optimal channel sensing strategy has
been analysed for the case when the ON-OFF time distributions of PU are
exponential. However, the analysis of recent spectrum measurement traces
reveals that PU exhibits heavy-tailed idle times which can be approximated well
with Hyper-exponential distribution (HED). In our work, we deduce the structure
of optimal sensing interval policy for channels with HED OFF times through
Markov Decision Process (MDP). We then use dynamic programming framework to
derive sub-optimal sensing interval policies. A new Multishot sensing interval
policy is proposed and it is compared with existing policies for its
performance in terms of number of channel sensing and interference to PU.
