基于噪声与干扰抑制的5G 波束检测算法与实现
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TN929.5

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国家重点研发计划高性能物联网综合测试仪(2022YFF0706700)项目资助


5G beam detection algorithm and implementation based on noise and interference suppression
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    摘要:

    针对5G外场测试中,同频多小区检测受噪声和干扰影响的问题,提出一种改进的阈值选取方法。算法通过分块计算 信噪比以及峰均比来确定检测门限,并且基于DFT 的信道估计算法可以进一步降低噪声对信号检测的影响。检测出首强小 区后,将其设为干扰信号,利用信号重构和干扰抑制算法,可以进一步提高有效5G小区的检测概率。在硬件实现上,充分利 用 DSP 的多核并行信号处理能力,进一步提升分块检测的效率。仿真实验对比了不同场景下所提算法与传统算法的检测结 果,平台实测验证了所提算法的有效性和可靠性。

    Abstract:

    In this paper,an improved threshold selection method is proposed to solve the problem that the same frequency multi-cell detection,which is affected by noise and interference in5G field testing.The detection threshold is determined by block calculation of signal-to-noise ratio and peak-to-average ratio,and the channel estimation algorithm based on DFT can further reduce the influence of noise on signal detection.After the first strong cell is detected,it is set as interference signal.Using signal reconstruction and interference elimination algorithm,the detection probability of effective 5G cell can be further improved.In hardware implementation,the multi-core parallel signal processing capability of DSP is fully utilized to further improve the efficiency of block detection.Simulation experiments compare the detection results of the proposed algorithm and the traditional algorithm under different scenarios,and the platform measurement verifies the effectiveness and reliability of the proposed algorithm.

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江 丹,刘祖深,安 宇 宁.基于噪声与干扰抑制的5G 波束检测算法与实现[J].国外电子测量技术,2023,42(4):31-37

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  • 在线发布日期: 2024-10-29
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