Blockage Intelligence in Complex Environments for Beyond 5G Localization
Blockage Intelligence in Complex Environments for Beyond 5G Localization
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DOI：
10.1109/jsac.2023.3275612
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发表时间：
2023-06
影响因子：
16.4
通讯作者：
Gianluca Torsoli;M. Win;A. Conti
中科院分区：
文献类型：
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作者：
Gianluca Torsoli;M. Win;A. Conti
位置感知对于无线生态系统中的若干应用至关重要，包括第五代（5G）和第三代合作伙伴计划（3GPP）定义的更高网络。然而，复杂的无线环境，如室内工厂的特点是苛刻的多径传播和非视距（NLOS）条件，这是有害的定位精度。本文引入阻塞智能（BI）的概念，提供一个概率描述的无线传播条件。然后，讨论了它在传统定位算法和基于软信息（SI）的定位算法中的集成。在具有各种gNodeB（gNB）部署的3GPP室内工厂场景中呈现案例研究。结果表明，BI与SI为基础的本地化显着优于现有的本地化技术。BI提供的丰富信息对于在复杂的无线环境中运行的5G及其他网络中执行准确定位至关重要。
Location awareness is vital for several applications in wireless ecosystems, including fifth generation (5G) and beyond networks defined by the 3rd Generation Partnership Project (3GPP). However, complex wireless environments such as indoor factories are characterized by harsh multipath propagation and non-line-of-sight (NLOS) conditions, which are detrimental to localization accuracy. This paper introduces the concept of blockage intelligence (BI) to provide a probabilistic description of wireless propagation conditions. Then, it discusses its integration in both conventional and soft information (SI)-based localization algorithms. Case studies are presented in the 3GPP indoor factory scenario with various gNodeBs (gNBs) deployments. Results show that BI together with SI-based localization significantly outperforms existing localization techniques. The rich information provided by BI is vital to perform accurate localization in 5G and beyond networks operating in complex wireless environments.