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In this paper, a cross-layer optimal scheduling algorithm for cooperative multi-hop Cognitive Radio Networks (CRNs) is presented, where secondary users (SUs) assist primary users' (PUs') multi-hop transmissions and in return gain an immediate time-share of the channel proportional to their assistance. While providing deterministic upper-bounds for PU queue backlogs, the proposed algorithm approaches the optimal PU throughput arbitrarily close, with a tradeoff in the average delay upper-bounds of flows. The analysis is further extended to a model with a more general "long-term reward mechanism", where a time-averaged share of the channel is guaranteed for SUs. The proposed algorithm provides order-optimal delay for the primary traffic. Distributed implementation issues have also been investigated. The properties of the proposed algorithm have also been illustrated through simulation studies.
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Xue et al. (2013) studied this question.
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