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Cooperative cognitive radio networks use cooperative relays to forward signal from the source to the destination. In cooperative cognitive radio networks, the transmission power of each relay is limited by the interference constraint of the primary user receiver. Thus, it is essential to optimize power allocation and multi-relay selection jointly to maximize the secondary system throughput. Optimizing multi-relay selection and power allocation requires an exhaustive search for all possible relay combinations, since this approach uses a large amount of valuable resources and entails high computational complexity. A suboptimal solution for power allocation may reduce the computational complexity but still involves high implementation complexity. Thus, for an efficient utilization of resources to support the applicability of cognitive radio for the Internet of things, we propose a low-complexity timer-based multi-relay selection that determines a forwarding relay set before the source begins to transmit its data. This allows the source to know the instantaneous channel state information of the relays, which helps the source to assign appropriate transmission power to the relays. By simulation, we show that the proposed scheme achieves near-optimal secondary system throughput performance to the optimal multi-relay selection as well as provides a significant secondary system throughput gain when compared to conventional and random relay selection scheme with equal power allocation.

Low-complexity timer-based multi-relay selection and sequential power allocation of cooperative cognitive radio networks for future Internet of things