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Throughput maximization-based optimal power allocation for energy-harvesting cognitive radio networks with multiusers

机译:基于吞吐量的基于最大化的能量收集认知无线电网络与多用户的最佳功率分配

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摘要

An optimal power allocation (OPA) policy for orthogonal frequency division multiplexing (OFDM)-based cognitive radio networks (CRNs) using underlay spectrum access model is presented under multiple secondary users (SUs) with energy harvesting (EH). The proposed algorithm can allocate transmission power to each SU on each subcarrier with the objective of maximizing the average throughput of secondary network over a finite time interval. We consider both the interference power constraint limited by primary user (PU) and the minimum throughput constraint of each SU to improve the throughput of SUs while guaranteeing the communication quality of PU. To balance current throughput and expected future throughput, a dynamic programming (DP) problem is defined and solved by the backward induction method. Moreover, for each time slot, a convex immediate optimization is presented to obtain an optimal solution, which can be solved by the Lagrange dual method. Simulation results show that our policy can achieve better performance than some traditional policies and ensure good quality of service (QoS) of PU when SUs access the spectrum.
机译:使用底层频谱接入模型的正交频分复用(OFDM)的正交频分复用(OFDM)的认知无线电网络(CRNS)的最佳功率分配(OPA)策略在具有能量收集(EH)的多个二级用户(SUS)下呈现。所提出的算法可以在每个子载波上分配到每个SU的传输功率,其目的是通过有限时间间隔最大化次要网络的平均吞吐量。我们考虑由主用户(PU)的干扰功率约束以及每个SU的最小吞吐量约束,以提高SUS的吞吐量,同时保证PU的通信质量。为了平衡当前吞吐量和预期的未来吞吐量,通过后向感应方法定义和解决动态编程(DP)问题。此外,对于每个时隙,呈现凸起立即优化以获得最佳解决方案,其可以通过拉格朗日双方法解决。仿真结果表明,我们的政策可以实现比某些传统政策更好的性能,并在SUS访问光谱时确保PU的良好服务质量(QoS)。

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