Coexistence between cellular systems and Wi-Fi gained the attention of the research community when LTE License Assisted Access (LAA) entered the unlicensed band. The recent introduction of NR-U as part of 5G introduces new coexistence opportunities because it implements scalable numerology (flexible subcarrier spacing and OFDM symbol lengths), and non-slot based scheduling (mini-slots), which considerably impact channel access. This paper analyzes the impact of NR-U settings on its coexistence with Wi-Fi networks and compares it with LAA operation using simulations and experiments. First, we propose a downlink channel access simulation model, which addresses the problem of the dependency and non-uniformity of transmission attempts of different nodes, as a result of the synchronization mechanism introduced by NR-U. Second, we validate the accuracy of the proposed model using FPGA-based LAA, NR-U, and Wi-Fi prototypes with over-the-air transmissions. Additionally, we show that replacing LAA with NR-U would not only allow to overcome the problem of bandwidth wastage caused by reservation signals but also, in some cases, to preserve fairness in channel access for both scheduled and random-access systems. Finally, we conclude that fair coexistence of the aforementioned systems in unlicensed bands is not guaranteed in general, and novel mechanisms are necessary for improving the sharing of resources between scheduled and contention-based technologies.


翻译:当LTE许可辅助访问(LAA)进入无许可证带时,蜂窝系统和Wi-Fi之间的共存得到了研究界的注意。最近推出的NR-U作为5G的一部分,引入了新的共存机会,因为它实施了可缩放的数字学(弹性子载波间距和DM符号长度),以及非基于时间的列表(微粒-地段),对频道访问有很大影响。本文分析了NR-U设置对其与Wi-Fi网络共存的影响,并利用模拟和实验将其与LAAAA业务进行比较。首先,我们建议采用下链通道访问模拟模型,解决不同节点传输尝试的依赖性和不一致性问题,因为NR-U采用了同步机制。 其次,我们用基于FGA的LAAA、NR-U和Wi-Fi原型模型对超空传输系统的影响进行了验证。我们用NRA-U取代LA-U将不仅能够克服带宽带宽的问题,而且由于公平性和保密性地共享技术而最终维持了频道系统的正常访问和保密性,因此,在保密系统之间也保持了保密,最后维持了保密性地交换系统。

0
下载
关闭预览

相关内容

Wi-Fi 是 Wi-Fi 联盟制造商的商标可做为产品的品牌认证,是一个创建于 IEEE 802.11 标准的无线局域网络(WLAN)设备。
Linux导论,Introduction to Linux,96页ppt
专知会员服务
75+阅读 · 2020年7月26日
[综述]深度学习下的场景文本检测与识别
专知会员服务
77+阅读 · 2019年10月10日
【SIGGRAPH2019】TensorFlow 2.0深度学习计算机图形学应用
专知会员服务
39+阅读 · 2019年10月9日
已删除
将门创投
4+阅读 · 2018年12月10日
Arxiv
0+阅读 · 2021年7月22日
VIP会员
相关资讯
已删除
将门创投
4+阅读 · 2018年12月10日
Top
微信扫码咨询专知VIP会员