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Throughput Maximization With Energy Harvesting in UAV-Assisted Cognitive Mobile Relay Networks

机译:无人机辅助认知移动继电器网络中的能量收集吞吐量最大化

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摘要

In order to extend the communication coverage and improve system performance, the applications of unmanned aerial vehicles (UAVs) in wireless communications have attracted a lot of attention in the industry. In this paper, we propose a power control algorithm in energy harvesting (EH)-based cognitive mobile relay networks where an UAV is equipped with a decode-and-forward (DF) relay to cooperate the communication of secondary user (SU). Assuming that the only power source for SU transmitter with EH is a battery with infinite capacity, we solve a throughput maximization problem to optimize the transmit powers of SU and the mobile relay, subject to the causality constraint of energy usage at SU transmitter, the maximum transmit power constraint of the mobile relay, and the interference temperature (IT) constraint to protect the communication of primary user (PU). When formulating this throughput maximization problem, we adopt an offline scheme with deterministic settings. For simplicity, the original multi-variable optimization problem is transformed into a single variable optimization problem via the optimal throughput principle of the DF relaying communication system. Furthermore, we solve this new optimization problem via the Lagrange dual method, and we derive the closed-form expressions of the optimal solutions. The simulation results illustrate the optimized system performance that the optimal throughput of the secondary system can be achieved by the proposed dynamic power control algorithm.
机译:为了延长通信覆盖并提高系统性能,无人信路(无人机)在无线通信中的应用引起了行业的重大关注。在本文中,我们提出了一种能量收集的功率控制算法(EH)的基于认知移动中继网络,其中UAV配备有解码和向前(DF)中继以协作辅助用户(SU)的通信。假设SU发射器的唯一电源是EH的电池是具有无限容量的电池,我们解决了一个吞吐量最大化问题,以优化SU和移动继电器的发射功率,但在SU发射器的能源使用的因果关系之外,最大值传输移动继电器的功率约束,以及干扰温度(IT)约束,以保护主用户(PU)的通信。在制定此吞吐量最大化问题时,我们采用具有确定性设置的离线方案。为简单起见,原始多变量优化问题通过DF中继通信系统的最佳吞吐量原理转换为单个变量优化问题。此外,我们通过拉格朗日双方法解决了这个新的优化问题,我们得出了最佳解决方案的封闭形式表达式。仿真结果说明了所提出的动态功率控制算法可以实现二次系统的最佳吞吐量的优化系统性能。

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