首页> 外文会议>IEEE Region 10 Conference >Traffic aware sleeping strategies for Small-Cell Base Station in the Ultra dense 5G Small Cell Networks
【24h】

Traffic aware sleeping strategies for Small-Cell Base Station in the Ultra dense 5G Small Cell Networks

机译:在超密集5G小型电池网络中的小型电池基站的交通意识休眠策略

获取原文

摘要

The 5G ultra-dense small cell network plays a key role in the future generation of mobile networks. It provides high data rate, seamless coverage and reliable services for wireless communication in an ultra-dense network. The dense deployment of small cells is needed to control forthcoming traffic demands which leads to enhance the operational cost and reduces the energy efficiency. One way to improve the energy efficiency is by using the sleeping strategy of small cell by transferring the traffic load of a small cell to other small cells. This work proposes an Initial Connection algorithm for establishing an initial association between the UEs and small base stations (s-BSs) while considering the UE preference. The Initial Connection algorithm creates a connected network. Moreover, the proposed Load Sharing Based Sleep Approach (LSBSA) algorithm performs small cells sleeping on the connected network which results in the deployment of s-BSs. The proposed Initial Connection and LSBSA algorithms are implemented and evaluated in MATLAB for different mobile data traffic. Also, various UEs distribution scenarios are considered. The results are demonstrated that the proposed approaches improve network performance in terms of energy efficiency of the small cell network by deploying the optimal number of active s-BSs.
机译:5G超密集的小型电池网络在未来的移动网络中起着关键作用。它为超密集网络中的无线通信提供了高数据速率,无缝覆盖范围和可靠的服务。需要进行小型电池的密集部署来控制即将到来的交通要求,这导致提高运营成本并降低了能源效率。通过将小细胞的交通负荷转移到其他小细胞来改善能量效率的一种方法是通过使用小细胞的睡眠策略。该工作提出了一种初始连接算法,用于在考虑UE偏好时在UE和小型基站(S-BSS)之间建立初始关联。初始连接算法创建连接的网络。此外,所提出的基于负载共享的睡眠方法(LSBSA)算法执行睡在连接网络上的小小区,从而导致S-BSS的部署。在MATLAB中实现和评估所提出的初始连接和LSBSA算法,用于不同的移动数据流量。此外,考虑了各种UE分发方案。结果表明,通过部署最佳数量的有源S-BSS,所提出的方法在小型电池网络的能效方面提高了网络性能。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号