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An improved graph coloring based small cell discovery scheme in LTE hyper-dense networks

机译:LTE超密集网络中基于小型小区发现方案的改进图

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Efficient discovery of multiple small cells is important to features such as small cell on/off, load balancing, CoMP (Coordinated Multi-point Transmission), e-ICIC (enhanced-Inter-Cell Interference Coordination) in LTE (Long Term Evolution) hyper-dense networks. However, severe interference in the Hyper-Dense Networks imposes great difficulty on efficient discovery of small cells. This paper proposes an improved graph coloring based scheme to facilitate the discovery of multiple small cells in Hyper-Dense Networks. Our proposed scheme is to divide small cells that are near to each other into different groups and let each group take turns to transmit synchronization signals so that interference between small cells are reduced. Graph coloring theory is employed in the division of small cells to guarantee that small cells within a certain distance are divided into different groups. Simulation results shows that using the proposed scheme detection probability of top 10 small cells is greatly improved compared to conventional scheme.
机译:有效发现多个小型电池对小电池开/关,负载平衡,COMP(协调多点传输),LTE(长期演进)超级电池(长期演进)的e-ICIC(增强群间干扰协调)等特征非常重要 - 阵列网络。然而,超密集网络的严重干扰对小细胞有效发现难以困难。本文提出了一种改进的基于图形着色方案,以便于在超密集网络中发现多个小单元。我们所提出的计划是将彼此附近的小小区分为不同的组,让每个组轮流转动以传输同步信号,以便减少小单元之间的干扰。图形着色理论用于小细胞的分割,以保证一定距离内的小细胞被分成不同的组。与传统方案相比,仿真结果表明,使用前10个小细胞的所提出的方案检测概率大大提高。

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