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Cooperative Spectrum Sharing With Wireless Energy Harvesting in Cognitive Radio Networks

机译:认知无线电网络中具有无线能量收集的协作频谱共享

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We study cooperative spectrum sharing in cognitive radio networks with wireless energy harvesting (EH), where all the primary and secondary users are overlaid on the 2-D plane. Each primary user (PU) should harvest energy from the wireless signal sent by its access point (AP), whereas all the APs and the secondary users have stable power supply. To improve EH efficiency, an EH zone is applied around each PU, where the secondary transmitter (ST) with the shortest distance toward the PU is selected to transfer the wireless energy. Using the harvested energy, the PU can transmit its data over the reverse link to the AP, but the data transmission is more likely to fail due to the weak transmission power and the severe path loss. In this case, a cooperative region is applied between each PU and its corresponding AP, where a suitable ST with the best channel quality toward the AP is selected to forward the primary data. The performance requirement of the primary system can be easily satisfied with ST cooperation, and thus, a fraction of bandwidth can be released to the secondary-data transmission. The optimization problem is formulated to maximize the area throughput of the secondary system under the performance constraint of the primary system. By analyzing system performance using the stochastic geometry theory, we propose an algorithm to optimally allocate the bandwidth and time resources to facilitate both the EH and data transmission. Performance results are presented to validate our theoretical analysis and show the impacts of various system settings.
机译:我们研究具有无线能量收集(EH)的认知无线电网络中的协作频谱共享,其中所有主要和次要用户都覆盖在二维平面上。每个主要用户(PU)应从其接入点(AP)发送的无线信号中获取能量,而所有AP和次要用户均具有稳定的电源。为了提高EH效率,在每个PU周围都应用了EH区域,在该区域中,选择了向PU距离最短的辅助发射机(ST)来传输无线能量。使用所收集的能量,PU可以通过反向链路将其数据传输到AP,但是由于传输功率弱和路径损耗严重,数据传输更有可能失败。在这种情况下,在每个PU与其对应的AP之间应用协作区域,其中选择具有朝向AP的最佳信道质量的合适的ST来转发主要数据。通过ST协作可以轻松满足主系统的性能要求,因此可以将一部分带宽释放给辅助数据传输。提出了优化问题,以在主系统的性能约束下最大化次系统的区域吞吐量。通过使用随机几何理论分析系统性能,我们提出了一种算法,可以优化分配带宽和时间资源,以促进EH和数据传输。给出性能结果以验证我们的理论分析并显示各种系统设置的影响。

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