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Cognitive spectrum access in macro-femto heterogeneous networks

机译:宏毫微微异构网络中的认知频谱访问

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Deploying femtocells over the conventional macrocell network is a promising way to increase network capacity, whereas the main bottleneck is the interference between the femtocell and macrocell tiers. Recent research has proposed many effective methods for cross-tier interference mitigation, but unfortunately, the optimal spectrum access scheme remains unknown. In this paper, a cognitive spectrum access scheme is proposed, where each femtocell can dynamically explore and access the idle macro-tier spectrum besides its dedicated femto-tier spectrum. The optimum probabilities for each femtocell to access the femto-tier and idle macro-tier spectrum which maximize the area spectral efficiency (ASE) are investigated. With perfect spectrum sensing, the ratio between the optimum probabilities to access the femto-tier and macro-tier spectrum is equal to the amounts of available subchannels in the femto-tier and macro-tier spectrum for most cases. With non-perfect spectrum sensing, a lower bound of the optimum probability to access the femto-tier spectrum is determined, which is a piecewise function of the femtocell intensity. Simulation results validate the accuracy of our analytical results and reveal the advantages of the proposed scheme over existing schemes.
机译:在常规宏小区网络上部署毫微微小区是增加网络容量的一种有前途的方法,而主要瓶颈是毫微微小区和宏小区层之间的干扰。最近的研究提出了许多有效的跨层干扰缓解方法,但不幸的是,最佳频谱接入方案仍然未知。在本文中,提出了一种认知频谱访问方案,其中每个毫微微小区除了可以使用其专用的毫微微层频谱之外,还可以动态地探索和访问空闲的宏层频谱。研究了使每个毫微微小区访问毫微微层和空闲宏层频谱的最佳概率,这些概率最大化了区域频谱效率(ASE)。通过完美的频谱感知,在大多数情况下,接入毫微微层和宏层频谱的最佳概率之比等于毫微微层和宏层频谱中可用子信道的数量。通过非完美频谱检测,可以确定进入毫微微蜂窝层频谱的最佳概率的下限,这是毫微微小区强度的分段函数。仿真结果验证了我们分析结果的准确性,并揭示了该方案相对于现有方案的优势。

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