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Robust Resource Allocation in NOMA based Cognitive Radio Networks

机译:基于Noma认知无线电网络的鲁棒资源分配

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In this paper, we propose a novel robust resource allocation algorithm for downlink non-orthogonal multiple access (NOMA) cognitive radio networks with the underlay spectrum sharing mode. To characterize the effect of channel uncertainty, a robust energy efficiency (EE) maximization optimization problem is formulated under the constraints of the maximum interference temperature threshold of primary user, the maximum transmit power of secondary base station, and the outage probability of secondary user’s rate. The non-linear optimization problem is converted into a convex form by using a new parameter transformation. Moreover, the analytical solution of power allocation is obtained by using the Lagrange dual theory. The provided results demonstrate the proposed robust resource allocation scheme can always achieve better EE and outage performance than that of the traditional orthogonal multiple access scheme and the non-robust NOMA scheme.
机译:在本文中,我们提出了一种具有底层频谱共享模式的下行链路非正交多址(NOMA)认知无线电网络的新颖的鲁棒资源配置算法。为了表征信道不确定性的影响,在主用户的最大干扰温度阈值的约束下,制定了强大的能量效率(EE)最大化优化问题,辅助基站的最大发射功率以及辅助用户速率的停电概率。使用新的参数转换将非线性优化问题转换为凸形。此外,通过使用拉格朗日双理论获得功率分配的分析解决方案。所提供的结果证明了所提出的稳健资源分配方案可以始终实现比传统的正交多址方案和非鲁棒NOMA方案的性能更好的EE和中断性能。

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