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Dynamic power allocation for spectrum sharing in interference alignment (IA)-based cognitive radio

机译:基于干扰对齐(IA)的认知无线电中频谱共享的动态功率分配

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In cognitive radio networks (CRN), underlay spectrum sharing allows secondary users (SUs) to utilize the spectrum on which the primary users (PUs) are working at the same time, without introducing intolerant interference. Interference alignment (IA) is a prospective technique for interference management, and can significantly improve the performance of cognitive radio (CR) networks. Besides, power allocation (PA) in IA-based CR networks is greatly neglected, which can further reinforce its performance. Thus in our paper, PA in IA-based CR networks is analyzed. To satisfy the QoS requirement of the PU, its minimal transmitted power is derived. To maximize the total rate of CRN and maintain the fairness between the competing SUs, the system is modeled as an optimization problem with the constraints of transmission power in IA-based cognitive radio. Based on this study, we propose the optimal transmission power allocation algorithm. Extensive simulation results show that the proposed optimal algorithm can improve the system capacity and maintain the fairness compared to the existing algorithms.
机译:在认知无线电网络(CRN)中,底层频谱共享使次要用户(SU)可以利用主要用户(PU)同时在其上工作的频谱,而不会引入不容忍的干扰。干扰对齐(IA)是一种用于干扰管理的前瞻性技术,可以显着提高认知无线电(CR)网络的性能。此外,基于IA的CR网络中的功率分配(PA)被大大忽略了,这可以进一步增强其性能。因此,在本文中,分析了基于IA的CR网络中的PA。为了满足PU的QoS要求,推导了其最小的发射功率。为了最大程度地提高CRN的总速率并维持竞争SU之间的公平性,将系统建模为一个优化问题,并在基于IA的认知无线电中限制了发射功率。在此研究的基础上,我们提出了最优的传输功率分配算法。大量的仿真结果表明,与现有算法相比,本文提出的最优算法可以提高系统容量并保持公平性。

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