链路仿真到系统仿真信噪比关键参数映射方法

2021 International Conference on Signal Processing and Machine Learning (CONF-SPML) Pub Date : 2021-11-01 DOI:10.1109/CONF-SPML54095.2021.00011

Jizhao Lei, Minghui Li, Yihui Jin, Di Zhao, Huijun Wang, Yunhe Liu, Ruiliang Song, Wenliang Lin, Ke Wang

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引用次数: 0

摘要

世界各地的研究机构计划建立一个连接星座配置和协议的仿真平台，以支持6G卫星通信系统关键技术的设计和验证。如何有效地传递链路级仿真和系统级仿真的参数，是提高仿真验证可靠性和效率的一个重要问题。本文通过对传统地基EESM算法进行优化，拟合了12种信道，得到了MCS下所有L2S接口参数$\beta$值，并提出了一种MCS进行$\beta$拟合验证，拟合效果满足3GPP规定的误差要求。基于子带加权CQI方法，通过各链路的仿真结果得到宽带CQI值。然后根据CQI值指定MCS-CQI映射表，通过映射表模拟链路自适应调整过程。最后利用反馈信噪比和CQI验证相应的BLER值是否满足小于10%的要求。

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Key Parameter Mapping Method of Signal-To-Noise Ratio from Link Simulation to System Simulation

Research institutions around the world plan to build a simulation platform that links constellation configuration and protocols together to support the design and verification of key technologies in 6G satellite communication systems. An important issue to improve the reliability and efficiency of simulation verification is how to effectively transfer the parameters of link-level simulation and system-level simulation. In this paper, by optimizing the traditional ground-based EESM algorithm, 12 kinds of channels are fitted, and all L2S interface parameter $\beta$ values under MCS are obtained, and a MCS is proposed for $\beta$ fitting verification, and the fitting effect meets the specified error Required by 3GPP. The wideband CQI value is obtained through the simulation results of all links and based on the subband weighted CQI method. Then specify the MCS-CQI mapping table according to the CQI value, and simulate the link adaptive adjustment process through the mapping table. Finally, the feedback SNR and CQI are used to verify whether the corresponding BLER value meets the requirement of less than 10%.

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2021 International Conference on Signal Processing and Machine Learning (CONF-SPML)

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