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

Sensing-Throughput Tradeoff for Superior Selective Reporting-based Spectrum Sensing in Energy Harvesting HCRNs