1.重庆邮电大学电子科学与工程学院,重庆400065
2.重庆邮电大学集成电路学院,重庆 400065
3.重庆邮电大学通信与信息工程学院,重庆 400065
[ "王华东 男,1977年生.博士,副教授.主要研究方向为无线通信系统非线性建模及补偿技术、毫米波雷达目标检测技术研究及实现等.E-mail: wanghuadong@cqupt.edu.cn" ]
[ "杨健鹏 男,2002年生.现为重庆邮电大学硕士研究生.主要研究方向为无线通信系统的非线性建模及盲辨识.E-mail: m17700644370@163.com" ]
[ "张天骐 男,1971年生.教授.主要研究方向为语音信号处理、通信信号的调制解调、盲处理、神经网络实现以及FPGA、VLSI实现.E-mail: zhangtq@cqupt.edu.cn" ]
收稿:2025-07-25,
录用:2025-11-05,
纸质出版:2025-11-25
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王华东, 杨健鹏, 张天骐. 基于判决重构的非线性卫星信道盲均衡算法[J]. 电子学报, 2025, 53(11): 4132-4141.
WANG Hua-dong, YANG Jian-peng, ZHANG Tian-qi. Blind Equalization Algorithm for Nonlinear Satellite Channels Based on Decision-Reconstruction[J]. Acta Electronica Sinica, 2025, 53(11): 4132-4141.
王华东, 杨健鹏, 张天骐. 基于判决重构的非线性卫星信道盲均衡算法[J]. 电子学报, 2025, 53(11): 4132-4141. DOI:10.12263/DZXB.20250653
WANG Hua-dong, YANG Jian-peng, ZHANG Tian-qi. Blind Equalization Algorithm for Nonlinear Satellite Channels Based on Decision-Reconstruction[J]. Acta Electronica Sinica, 2025, 53(11): 4132-4141. DOI:10.12263/DZXB.20250653
由于卫星通信系统中高功率放大器的非线性失真与多径信道的线性衰落效应相互耦合会引发传输性能恶化问题,而传统的盲均衡算法(如恒模算法)虽在应对多径引起的线性符号间干扰时具有一定效果,但无法有效补偿高阶调制信号中的非线性失真,尤其是在没有训练序列的盲均衡场景下,传统方法难以提供足够的监督信息.为了克服这一挑战,本文提出一种基于判决重构的非线性卫星信道盲均衡算法(blind Equalization Algorithm for Nonlinear satellite channels based on Decision-Reconstruction,DR-NEA),DR-NEA采用判决-插值-重构模式生成参考信号,从而实现无监督条件下的非线性与线性失真联合补偿.首先,算法通过恒模算法对接收到的信号进行线性均衡,消除多径效应引起的线性失真.随后,通过判决、插值和重构生成参考信号,该参考信号为非线性均衡器参数辨识提供监督信息.最后,DR-NEA使用拟牛顿法在最小均方误差准则下对Wiener型均衡器的参数进行辨识,进而实现对信道中的线性与非线性失真联合补偿.仿真结果表明,在高阶调制模式(32APSK、32QAM、64QAM)下,DR-NEA相较于传统线性均衡算法,显著提升了性能,在误码率为
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时,较传统线性均衡算法性能增益超4 dB,体现了该算法在高阶调制下较强的非线性补偿能力.此外,当判决误码率低于9.44%时,DR-NEA依旧保持稳定且输出性能几乎不受影响,进一步验证了本文算法的鲁棒性.DR-NEA通过创新性地引入基于判决重构的参考信号生成方法,解决了传统盲均衡算法无法提供足够监督信息的问题.同时,采用拟牛顿法进行Wiener模型参数辨识,实现了高效的非线性均衡器优化.实验结果验证了该算法在非线性与线性失真补偿方面的优越性能,特别适用于高阶调制信号的传输.综上所述,DR-NEA算法有效解决了卫星通信中非线性失真与多径衰落的联合干扰问题,具有重要的理论意义和广泛的实际应用前景,特别是在高速率、高阶调制的卫星通信场景中,能够显著提升系统的传输性能.
For the transmission performance degradation problem caused by the coupling of nonlinear distortion from high-power amplifiers and linear fading effects of multipath channels in satellite communication systems
traditional blind equalization algorithms
such as the constant modulus algorithm (CMA)
have a certain effect in addressing linear intersymbol interference caused by multipath. However
the traditional methods cannot effectively compensate for nonlinear distortion in high-order modulated signals
especially in blind equalization scenarios without training sequences
making it difficult to provide sufficient supervision information.To overcome this challenge
this paper proposes a blind equalization algorithm for nonlinear satellite channels based on decision-reconstruction (DR-NEA). DR-NEA adopts a decision-interpolation-reconstruction mode to generate reference signals
thereby realizing the joint compensation of nonlinear and lin
ear distortions under unsupervised conditions. Firstly
the algorithm performs linear equalization on the received signal through the CMA to eliminate linear distortion caused by multipath effects. Subsequently
a reference signal is generated through decision
interpolation and reconstruction
providing supervision information for the parameter identification of the nonlinear equalizer. Finally
DR-NEA uses the Quasi-Newton method to identify the parameters of the Wiener-type equalizer under the criterion of minimum mean square error
thereby realizing the joint compensation of linear and nonlinear distortions in the channel. Simulation results show that under high-order modulation modes (32APSK
32QAM
64QAM)
the traditional linear equalization algorithms are outperformed by DR-NEA. When the bit error rate is
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9.48266602
2.53999996
its performance gain is more than 4 dB compared with traditional linear equalization algorithms
which reflects its strong nonlinear compensation capability under high-order modulation. In addition
when the decision error rate is lower than 9.44%
DR-NEA still maintains stability and its output performance is hardly affected
which further verifies the robustness of the proposed algorithm.By innovatively introducing a reference signal generation method based on decision reconstruction
DR-NEA solves the problem
that traditional blind equalization algorithms cannot provide sufficient supervision information. At the same time
it adopts the Quasi-Newton method for Wiener model parameter identification
realizing efficient optimization of the nonlinear equalizer. Experimental results verify the superior performance of this algorithm in compensating nonlinear and linear distortions
and it is particularly suitable for the transmission of high-order modulated signals. In summary
the DR-NEA algorithm effectively solves the problem of joint interference of nonlinear distortion and multipath fading in satellite communication
and has important theoretical significance and broad practical application prospects. Especially in high-data-rate and high-order modulation satellite communication scenarios
it can significantly improve the transmission performance of the system.
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