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Outage and energy efficiency analysis for cognitive based heterogeneous cellular networks

机译:基于认知的异构蜂窝网络的中断和能效分析

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摘要

Cognitive radio and small cells are the promising techniques to minimize energy consumption and satisfy the exponentially increasing data rates for the heterogeneous cellular network (HCN). In this paper, a theoretical framework is developed to calculate the outage probability of the HCN based on the opportunistic utilization of the traditional cellular bandwidth and television white space (TVWS) for the cognitive femto base stations. This work investigates overlay, underlay, mixed overlay-underlay based two tiers cognitive HCN. It also investigates the impact of the TVWS in the overlay-TVWS mixed spectrum sharing technique (SST). Tools from stochastic geometry are used to model cognitive HCN. Furthermore, the tier selection probability, average ergodic rate, area spectral efficiency (ASE), and energy efficiency (EE) of the HCN are also calculated for different SSTs. Numerical results show that mixed SST achieves a significant reduction in tier outage probability and total outage probability as compared to underlay and overlay techniques alone. It is also demonstrated that compared to the traditional single tier network, cognitive based HCN can improve the total ASE and EE of the order of and 10, respectively.
机译:认知无线电和小型蜂窝小区是使能源消耗最小化并满足异构蜂窝网络(HCN)指数级增长的数据速率的有前途的技术。本文基于认知蜂窝基站的传统蜂窝带宽和电视空白空间(TVWS)的机会利用,开发了一种理论框架来计算HCN的中断概率。这项工作研究基于两层认知HCN的叠加,底层,混合叠加-底层。它还研究了TVWS在覆盖TVWS混合频谱共享技术(SST)中的影响。随机几何中的工具可用于对认知HCN进行建模。此外,还针对不同的SST计算了HCN的层选择概率,平均遍历率,面积谱效率(ASE)和能量效率(EE)。数值结果表明,与单独的底层和叠加技术相比,混合SST显着降低了层中断概率和总中断概率。还证明,与传统的单层网络相比,基于认知的HCN可以将ASE和EE的总值分别提高大约10和10。

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