  In this paper, we investigate the performance of conventional cooperative
sensing (CCS) and superior selective reporting (SSR)-based cooperative sensing
in an energy harvesting-enabled heterogeneous cognitive radio network (HCRN).
In particular, we derive expressions for the achievable throughput of both
schemes and formulate nonlinear integer programming problems, in order to find
the throughput-optimal set of spectrum sensors scheduled to sense a particular
channel, given primary user (PU) interference and energy harvesting
constraints. Furthermore, we present novel solutions for the underlying
optimization problems based on the cross-entropy (CE) method, and compare the
performance with exhaustive search and greedy algorithms. Finally, we discuss
the tradeoff between the average achievable throughput of the SSR and CCS
schemes, and highlight the regime where the SSR scheme outperforms the CCS
scheme. Notably, we show that there is an inherent tradeoff between the channel
available time and the detection accuracy. Our numerical results show that, as
the number of spectrum sensors increases, the channel available time gains a
higher priority in an HCRN, as opposed to detection accuracy.
