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基于低轨卫星PCMA信号的信道估计算法研究
Research on Channel Estimation Algorithm based on LEO Satellite PCMA Signal
- 光通信研究 2024年第3期 页码：23002301-23002306
- 作者机构：
南京邮电大学 通信与信息工程学院，南京 210003
- 作者简介：
王宇琦（1999-），男，安徽阜阳人。硕士，主要研究方向为卫星通信。
刘子威，副教授。E-mail：lzw@njupt.edu.cn
- 基金信息：国家自然科学基金资助项目(62171234;U21A20450;61971440);江苏省前沿引领技术基础研究专项资助项目(BK20192002)
DOI：10.13756/j.gtxyj.2024.230023
中图分类号： TN927纸质出版日期：2024-06-10，
收稿日期：2023-02-19，
修回日期：2023-02-27，
扫 描 看 全 文
王宇琦，江诗禹，刘子威，等.基于低轨卫星PCMA信号的信道估计算法研究[J].光通信研究，2024（3）：230023.
Wang Y Q, Jiang S Y, Liu Z W, et al. Research on Channel Estimation Algorithm based on LEO Satellite PCMA Signal[J]. Study on Optical Communications, 2024（3）：230023.
王宇琦，江诗禹，刘子威，等.基于低轨卫星PCMA信号的信道估计算法研究[J].光通信研究，2024（3）：230023. DOI： 10.13756/j.gtxyj.2024.230023.
Wang Y Q, Jiang S Y, Liu Z W, et al. Research on Channel Estimation Algorithm based on LEO Satellite PCMA Signal[J]. Study on Optical Communications, 2024（3）：230023. DOI： 10.13756/j.gtxyj.2024.230023.
摘要
【目的】
2
随着天地一体化信息网络的发展，低轨卫星通信系统迎来发展热潮，成对载波多址（PCMA）技术凭借其节省带宽资源的优点也逐渐向低轨卫星通信发展。然而，传统PCMA技术多用于高轨卫星中，无法适应低轨卫星信道高动态的衰落信道特性，使得PCMA接收端误码性能大大下降，其中的瓶颈在于重叠信号的信道估计与均衡技术。
【方法】
2
针对低轨卫星信道特点，文章提出了一种联合训练序列估计与自回归（AR）模型预测的信道估计方案。借鉴叠加训练序列信道估计的思想，引入了适用于PCMA混合信号信道估计的迭代方法，通过迭代提升训练序列信道估计的精确度；并利用AR模型实时预测数据序列的信道状态信息（CSI），同时也通过AR模型预测达到降低训练序列信道估计频次的目的，以适应低轨卫星信道的动态性。
【结果】
2
仿真结果表明，叠加训练序列信道估计的思路可以适用于PCMA信号中，经过迭代可以获得精确信道估计值。文章所提方法可以有效提高信道估计的精确性，且经过信号分离以及解调后，在信噪比
>
9 dB时误码率可以达到10
-3
量级。
【结论】
2
文章所提信道估计方案并入PCMA接收方案中后，误码率损失在可接受范围内，可以支持PCMA技术在低轨卫星通信中的应用，算法结构简单，复杂度低，具有实际可行性。
Abstract
【Objective】
2
With the development of the space-ground integrated information network
the Low Earth Orbit (LEO) satellite communication system is ushering in a development boom. The Paired Carrier Multiple Access (PCMA) technology is gradually developing to the low-orbit satellite communication due to its advantages of saving bandwidth resources. However
traditional PCMA technology is mostly used in high-orbit satellites
and cannot adapt to the highly dynamic fading channel character-istics of low-orbit satellite channels
which greatly degrades the bit error performance of the PCMA receiver. The bottleneck lies in the channel estimation and equalization technologies for overlapping signals.
【Methods】
2
Aiming at the channel characteristics of LEO satellites
this paper proposes a channel estimation scheme that combines training sequence estimation and Autoregressive (AR) model prediction. Based on the idea of superimposed training sequence channel estimation
an iterative method suitable for PCMA mixed signal channel estimation is introduced to improve the accuracy of training sequence channel estimation through iteration. The AR model is used to predict the Channel State Information (CSI) of the data sequence in real time. The use of AR model can also reduce the frequency of channel estimation in training sequences
so as to adapt to the dynamics of LEO satellite channels.
【Results】
2
The simulation results show that the idea of superimposed training sequence channel estimation can be applied to the PCMA signals
and accurate channel estimation can be obtained after iterations. The method proposed in this paper can effectively improve the accuracy of channel estimation. After signal separation and demodulation
the bit error rate can reach the order of 10
-3
when the signal-to-noise ratio is greater than 9 dB.
【Conclusion】
2
A channel estimation method for PCMA signal is proposed in this paper. The simulation results show that the bit error rate loss is within an acceptable range
which can support the application of PCMA technology in low-orbit satellite communication. The proposed algorithm has the advantages of simple structure
low complexity
and high practical value.
关键词
低轨卫星成对载波多址信道估计自回归模型
Keywords
LEO satellitePCMAchannel estimationAR model
references
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