In this paper, the authors consider an underlay multi-hop cognitive radio network with energy harvesting secondary nodes, where there is a cluster of secondary decode-and-forward relays in each hop. The secondary nodes have no separate energy source available with them, but wake up from idle mode to harvest energy from the primary signal with the time-switching protocol, and use it for transmitting/relaying using the peak interference constraint. In each cluster, a relay with maximum transmit power is selected except in the last one. In the last cluster, a relay which has a maximum signal-to-noise ratio (SNR) at the secondary destination is selected. Though the suggested scheme has low implementation complexity and requires very little channel estimation, its performance is close to that of a scheme in which the link with the best SNR is chosen in each hop (which requires a lot of channel estimation). Analytical expressions are derived for the end-to-end outage probability and throughput assuming Rayleigh faded channels. They show that it is important to optimise the time-switching parameter (fraction of time devoted to energy harvesting) and the number of hops. Simulations confirm the accuracy of the derived expressions.

中文翻译：

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具有能量收集节点的基于集群的多跳底层网络的性能

在本文中，作者考虑了具有能量收集次级节点的底层多跳认知无线电网络，其中每跳中都有一组次级解码和转发中继。次要节点没有可用的单独能源，但会从空闲模式中唤醒，以使用时间切换协议从主要信号中收集能量，并使用峰值干扰约束将其用于传输/中继。在每个集群中，除了最后一个集群外，都会选择具有最大发射功率的中继。在最后一个群集中，选择在次要目的地具有最大信噪比（SNR）的中继。尽管建议的方案实现复杂度较低，并且需要很少的信道估计，它的性能接近于在每跳中选择具有最佳SNR的链路的方案（需要大量的信道估计）。假设瑞利衰落信道，则得出端到端中断概率和吞吐量的解析表达式。他们表明，优化时间切换参数（专门用于能量收集的时间分数）和跳数非常重要。仿真证实了导出表达式的准确性。