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Optimal spectrum access and power control of secondary users in cognitive radio networks

机译:认知无线电网络中次要用户的最佳频谱访问和功率控制

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In future 5G communication system, radio resources can be effectively reused by cognitive radio networks (CRNs), where a lot of secondary users (SUs) are able to access the spectrum of primary users (PUs). In this paper, we analyze the optimal spectrum access and power control of SUs on multiple bands with the target of maximizing the average sum rate (ASR) of SUs. Specifically, based on the stochastic geometry, the random distributions of PUs and SUs are modeled by Poisson point processes (PPPs), based on which we derive out the closed-form outage probabilities and obtain the ASR of SUs. Then, we formulate the maximization problem of ASR on multiple bands under the constraints of outage probabilities. With the help of convex optimization, the optimal density of SUs is obtained in closed-form when the power of SUs is fixed. The convexity of ASR is also verified, and we evaluate the optimal power of SUs when the density of SUs is fixed. Based on these two obtained results, a spectrum access and power control algorithm is further proposed to maximize the ASR of SUs on multiple bands. Simulation results demonstrate that the proposed algorithm can achieve a higher maximum ASR of SUs over the average power allocation algorithm, and the density and power boundary of SUs are constrained by PUs as well as the interference in the networks.
机译:在未来的5G通信系统中,认知资源网络(CRN)可以有效地重用无线电资源,其中许多辅助用户(SU)能够访问主要用户(PU)的频谱。在本文中,我们以最大化SU的平均总和(ASR)为目标,分析了多个频段上SU的最佳频谱接入和功率控制。具体而言,基于随机几何,通过泊松点过程(PPP)对PU和SU的随机分布进行建模,在此基础上,我们可以得出闭合形式的停电概率并获得SU的ASR。然后,在中断概率的约束下,提出了多频带ASR的最大化问题。借助于凸优化,当SU的功率固定时,可以以闭合形式获得SU的最佳密度。还验证了ASR的凸性,并且当SUs的密度固定时,我们评估了SUs的最佳功率。基于获得的两个结果,进一步提出了一种频谱接入和功率控制算法,以最大化SU在多个频带上的ASR。仿真结果表明,与平均功率分配算法相比,所提算法具有更高的SU最大ASR,并且SU的密度和功率边界受PU以及网络干扰的约束。

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