不完全频谱感知下认知机会接入飞基站的资源管理

Haijun Zhang, Chunxiao Jiang, Xiaotao Mao, A. Nallanathan
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引用次数: 7

摘要

近年来,基于认知无线电的飞蜂窝技术被认为是一种很有前途的无线通信技术,其资源分配和干扰管理问题得到了广泛的研究。然而,现有的研究大多忽略了频谱感知误差。本文提出了一种基于正交频分多址(OFDMA)的认知飞基站资源分配方案。目标是在不完全信道感知的QoS约束和协层/跨层干扰约束下最大化所有飞蜂窝用户(FUs)的和速率。首先将子信道和功率分配问题建模为一个混合整数规划问题,然后通过放宽子信道共享和施加协层干扰约束,将子信道和功率分配问题转化为一个凸优化问题,最后利用对偶分解方法进行求解。在此基础上,提出了一种迭代子信道和功率分配算法。通过仿真验证了该算法在瞬时最大可达率方面的有效性。
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Resource management in cognitive opportunistic access femtocells with imperfect spectrum sensing
Recently, cognitive radio enabled femtocell is regarded as a promising technique in wireless communications, where the issues of resource allocation and interference management have been investigated intensively. However, spectrum sensing errors are neglected in most of the existing works. In this paper, we propose a resource allocation scheme for orthogonal frequency division multiple access (OFDMA) based cognitive femtocells. The target is to maximize the sum rate of all femtocell users (FUs) under QoS constraints and co-tier/cross-tier interference constraints under imperfect channel sensing. The subchannel and power allocation problem is first modeled as a mixed integer programming problem, and then transformed into a convex optimization problem by relaxing subchannel sharing and imposing co-tier interference constraints, which is finally solved using the dual decomposition method. Based on the obtained solution, an iterative subchannel and power allocation algorithm is proposed. The effectiveness in terms of instantaneous maximum achievable rate of the proposed algorithm as compared with perfect spectrum sensing schemes is verified by simulations.
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