论文标题
5G NR初始访问中基于压缩感应的光束检测
Compressed-Sensing based Beam Detection in 5G NR Initial Access
论文作者
论文摘要
为了支持蜂窝通信中的毫米波（MMWave）频带，基站和移动平台都利用大型天线阵列将狭窄的光束转向彼此，以补偿路径损失并提高通信性能。但是，分配给初始访问的时频资源是有限的，这导致需要有效的梁检测方法。对于用于减少功耗的混合模拟数字波束形成（HB）架构，我们提出了一种基于压缩感应（CS）的方法，用于5G初始访问光束检测，该方法适用于HB体系结构，并且符合3GPP标准。将基于CS的方法与光束检测准确性方面的详尽搜索进行了比较，并且通过模拟表现出胜过表现。考虑到多达256个天线，重申了仔细的代码书设计的重要性。
To support millimeter wave (mmWave) frequency bands in cellular communications, both the base station and the mobile platform utilize large antenna arrays to steer narrow beams towards each other to compensate the path loss and improve communication performance. The time-frequency resource allocated for initial access, however, is limited, which gives rise to need for efficient approaches for beam detection. For hybrid analog-digital beamforming (HB) architectures, which are used to reduce power consumption, we propose a compressed sensing (CS) based approach for 5G initial access beam detection that is for a HB architecture and that is compliant with the 3GPP standard. The CS-based approach is compared with the exhaustive search in terms of beam detection accuracy and by simulation is shown to outperform. Up to 256 antennas are considered, and the importance of a careful codebook design is reaffirmed.
