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

机译:LTE超密集网络中基于图着色的改进小小区发现方案

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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:多个小小区的有效发现对于诸如LTE(长期演进)超级系统中的小小区开/关,负载均衡,CoMP(协作多点传输),e-ICIC(增强的小区间干扰协调)之类的功能很重要。密集网络。但是,在超密集网络中的严重干扰给有效发现小型小区带来了很大的困难。本文提出了一种改进的基于图着色的方案,以促进在超密集网络中发现多个小小区。我们提出的方案是将彼此靠近的小小区划分为不同的组,并让每个组轮流发送同步信号,从而减少小小区之间的干扰。图形着色理论用于小单元格的划分,以确保将一定距离内的小单元格划分为不同的组。仿真结果表明,与传统方案相比,使用所提出的方案对前10个小小区的检测概率大大提高。

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