Research on Channel Estimation Algorithm based on LEO Satellite PCMA Signal

WANG Yuqi; JIANG Shiyu; LIU Ziwei; ZHANG Gengxin

doi:10.13756/j.gtxyj.2024.230023

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Research on Channel Estimation Algorithm based on LEO Satellite PCMA Signal

更新时间：2024-05-30

- Research on Channel Estimation Algorithm based on LEO Satellite PCMA Signal
- Study on Optical Communications Issue 3, Pages: 23002301-23002306(2024)
- 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：
- 基金信息：
- DOI：10.13756/j.gtxyj.2024.230023
  CLC： TN927
- Published：10 June 2024，
  
  Received：19 February 2023，
  
  Revised：27 February 2023，
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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】

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】

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】

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】

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】

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】

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】

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】

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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