基于记忆多项式的Volterra混合均衡器设计与研究
Design and Study of Memory Polynomial-based Volterra Hybrid Equalizer
贾科军 1雷蕾 1蔺莹 1余彩虹2
作者信息
- 1. 兰州理工大学计算机与通信学院,兰州 730050
- 2. 福建工程学院电子电气与物理学院,福州 366000
- 折叠
摘要
[目的]发光二极管(LED)的非线性特性导致可见光通信(VLC)系统的误码率(BER)性能恶化,特别是在具有较高峰均功率比(PAPR)的光正交频分复用(O-OFDM)系统中.基于Volterra级数的单级均衡器可以处理LED非线性高阶失真,且延时较小.但是求解传统Volterra级数需要多重积分运算,基于Volterra级数的均衡器实现复杂度高,且单级均衡器存在误差累积,因此均衡抑制效果有限.[方法]首先,针对传统Volterra级数计算复杂度高的问题,只保留Volterra级数中各阶非线性项和内核系数的高阶幂级数项,提出了基于记忆多项式的Volterra级数(MPVS).相比于传统Volterra级数降低了计算复杂度,同时考虑了当前时刻的所有输入信号,提高了非线性系统建模的精度.然后,设计基于记忆多项式的Volterra(MPV)均衡器和基于记忆多项式的Volterra判决反馈均衡器(MPV-DFE),对于单级MPV-DFE,若判决部分一个码元判断错误,那么这种错误会连续成串出现,导致整个码元序列受到影响.文章提出将MPV和MPV-DFE两个非线性均衡器级联构成混合后均衡器(MPV+MPV-DFE).MPV 均衡器对 LED 非线性失真信号一级均衡,可以抑制一部分非线性失真,从而减少MPV-DFE码元判断错误.再经过 MPV-DFE二次均衡,可以更好地抑制残留的非线性失真.[结果]最后,采用蒙特卡洛BER仿真方法验证系统设计的有效性.结果表明:与单级MPV均衡器、线性级联非线性混合均衡器(LMS+MPV-DFE)相比,在 4 阶正交幅度调制(QAM)非对称限幅光OFDM(ACO-OFDM)系统BER为 10-4 时,所提混合均衡器分别可以获得大约 7 和 2dB的信噪比增益.[结论]MPV均衡器实现简单,且将两级非线性均衡器级联设计混合均衡器可以更好地抑制LED非线性失真.
Abstract
[Objective]The non-linear characteristics of Light Emitting Diodes(LEDs)contribute to the degradation of Bit Error Rate(BER)performance in Visible Light Communication(VLC)systems,particularly in Optical Orthogonal Frequency Division Multiplexing(O-OFDM)systems with high Peak-to-Average Power Ratio(PAPR).A single-stage equalizer based on the Volterra series can handle the high-order non-linear distortions of LEDs with low latency.However,solving the traditional Volt-erra series necessitates multiple integration operations,resulting in the high implementation complexity of the Volterra-based equalizer.Additionally,the single-stage equalizer accumulates errors with limited performance improvements.[Methods]Firstly,to address the issue of high computational complexity in the traditional calculations of the Volterra series,a proposition is made to retain only the high-order power series terms of the various nonlinear terms and kernel coefficients within the Volterra series.This approach,known as the Memory Polynomial-based Volterra Series(MPVS),not only reduces the computational complexity compared to the traditional Volterra series but also enhances the accuracy of nonlinear system modeling by considering all input sig-nals at the current moment.Subsequently,the design of channel equalizer considers the Memory Polynomial-based Volterra(MPV)equalizer and the Memory Polynomial-based Volterra Decision Feedback Equalizer(MPV-DFE).For a single-stage MPV-DFE,if an error occurs in the decision part leading to an incorrect symbol decoding,this error tends to manifest as a consec-utive series of errors,thereby impacting the entire symbol sequence.To mitigate this,a proposal is made to cascade the two non-linear equalizers,MPV and MPV-DFE,forming a hybrid equalizer called MPV+MPV-DFE.The MPV equalizer performs a primary equalization on the LED's nonlinear distortion signal,effectively suppressing a portion of the non-linear distortions and thereby reducing symbol decoding errors in the MPV-DFE.Subsequently,a secondary equalization is carried out by the MPV-DFE,leading to improved suppression of residual nonlinear distortions.[Results]Finally,the effectiveness of the system design was validated using Monte Carlo simulation to analyze the BER.The results demonstrate that compared to the single-stage MPV equalizer and the linear-cascade nonlinear hybrid equalizer(LMS+MPV-DFE),the proposed hybrid equalizer achieves approxi-mately 7 dB and 2 dB Signal-to-Noise Ratio(SNR)gains,respectively,in a 4 Quadrature Amplitude Modulation(QAM)-mod-ulated Asymmetrically Clipped Optical OFDM(ACO-OFDM)system at a BER of 10-4.[Conclusion]In conclusion,the imple-mentation of the MPV equalizer is straightforward,and the cascaded design of the two-stage nonlinear equalizers as a hybrid equalizer enables better mitigation of the LED's nonlinearity.
关键词
可见光通信/发光二极管非线性/沃尔泰拉级数/混合后均衡器Key words
VLC/LED nonlinear/Volterra series/hybrid post equalizer引用本文复制引用
基金项目
国家自然科学基金(61461026)
甘肃省科技计划(22JR5RA276)
甘肃省科技计划(22JR5RA274)
甘肃省科技计划(23YFGA0062)
甘肃省科技计划(2022A-215)
兰州理工大学博士科研启动基金(061903)
出版年
2024
国家科技期刊平台
NSTL
万方数据