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Subchannel and power allocation for OFDMA-based mobile cognitive radio networks

机译:基于OFDMA的移动认知无线电网络的子信道和功率分配

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Recently, researches on mobile cognitive radio network (CRN) has been paid more attention to, involving spectrum sensing, power control and spectrum access, while no schemes considering both the power and spectrum assignment at the same time. In this paper, an efficient resource allocation (RA) scheme is proposed for the orthogonal frequency division multiple access (OFDMA)-based mobile underlay CRN. Through location-awareness techniques, a realistic model based on predictable channel state information (CSI) is considered. According to the predicting result, the sum average effective capacity (EC) of the secondary network is calculated and aimed to be maximized through the RA scheme. Meanwhile the interference introduced to primary users (PUs) should be less than given thresholds, the signal to interference plus noise ratio (SINR) requirements and the limit of total transmit power of secondary users (SUs) should be satisfied. A stepwise algorithm is introduced to solve the optimization RA at the cost of a low complexity, with four procedures including access control, initial power allocation, subchannel allocation and power allocation. Simulation results demonstrate that the proposed algorithm can achieve not only higher total EC but also higher energy efficiency (EE) and spectrum efficiency (SE).
机译:最近,对移动认知无线电网络(CRN)的研究已引起更多关注,涉及频谱感测,功率控制和频谱访问,而没有同时考虑功率和频谱分配的方案。本文针对基于正交频分多址(OFDMA)的移动底层CRN,提出了一种有效的资源分配(RA)方案。通过位置感知技术,可以考虑基于可预测信道状态信息(CSI)的现实模型。根据预测结果,计算二次网络的总平均有效容量(EC),并旨在通过RA方案使其最大化。同时,引入到主要用户(PU)的干扰应小于给定的阈值,应满足信噪比(SINR)的要求以及次要用户(SU)的总发射功率的限制。引入了一种逐步算法,以低复杂度为代价来求解优化RA,并通过四个过程进行访问控制,初始功率分配,子信道分配和功率分配。仿真结果表明,该算法不仅可以实现更高的总EC,还可以实现更高的能量效率(EE)和频谱效率(SE)。

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