非线性卫星信道下的粒子滤波盲均衡方法

Particle Filtering Blind Equalization Method in Nonlinear Satellite Channel

  • 摘要: 针对卫星信道中高功率放大器产生非线性失真的问题,本文提出了一种基于粒子滤波技术的盲均衡法。该算法优势在于不需要对非线性信道线性化处理,而是利用带权值的离散随机样本点来对期望分布进行近似,通过将非线性模型建模成状态空间模型,对信道参数进行跟踪和符号序列估计。仿真结果表明,算法实现了对放大器非线性幅度和相位特性的粒子滤波估计,并对符号序列进行了盲恢复,在误比特率为 较截断Volterra均衡有1.5 dB左右的性能增益;通过增加粒子数目和平滑长度能一定程度上提高算法性能,但在复杂度与性能折中考虑下,不能无限增加粒子数目。

     

    Abstract: Contraposed that the high power amplifier produced nonlinear distortion in satellite channel, this paper proposed a particle filtering blind equalization method. Advantage of this method based on particle filtering is not to linearize the nonlinear channel, but using numbers of discrete random sample points with weighted values to approximate the expected distribution. Through modeling nonlinear model as a state space model, particle filtering can track the channel parameters and estimate the emitted symbol sequence .The simulation results show that the algorithm accomplished particle filtering estimation of the amplifier nonlinear characteristic of amplitude and phase, the restoration of the symbol sequence. Compared with truncate Volterra equalization , particle filtering algorithm obtained about 1.5 dB performance gain at the bit error rate of ; it can improve the performance of the algorithm by increasing the particle number and smooth length to a certain extent; but the complexity and performance tradeoffs to consider, it can’t infinitely increase the particle number.

     

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