基于复合分段模型的数字预失真技术

    Digital Predistortion Technology Based on Composite Piecewise Function Model

    • 摘要: 针对宽带功率放大器非线性与记忆效应校正问题,文中在矢量选择模型的基础上提出了一种基于复合分段模型的数字预失真技术。根据功放非线性失真特性对输入信号计算两个包络值阈值,并进行分段处理。其中,低段采用广义多项式(GMP)模型,中间段采用记忆多项式(MP)模型,而高段则采用更高阶GMP模型。所提分段模型间通过复用基础MP多项式,结合各段配置不同交叉项、记忆深度以及多项式阶数的设计方法,能够实现较好的线性化效果,同时降低了参数提取复杂度,并且降低了分段模型在分段点处的函数不连续影响。此外,文中所提模型可以针对不同的功放模型动态地调整阈值,具有更高的灵活性。仿真实验表示所提模型预失真后功放输出信号的邻道功率抑制比从-34.1 dBc提升至-46.5 dBc,性能与GMP相当,相较于MP模型提高了3.5 dB。矢量幅度误差表现从6.46%降低至1.06%,相较于MP模型提高了约0.7%。同时,参数提取复杂度较GMP模型降低了77%。

       

      Abstract: This paper presents a composed piecewise function digital predistortion model based on vector switch model to address the problem of substantial nonlinearity and strong memory effect in wideband power amplifier (PA). This paper sets two thresholds according to the PA characteristics and decompose the input signal into sub-signals by using two thresholds. In low stage, we use a generalized memory polynomial (GMP). A memory polynomial (MP) model was used in the middle stage and a higher-order GMP model was used in the high stage. By sharing the fundamental MP and configuring various cross terms, memory depth, and nonlinear degree for each segment, the proposed model improves linearization performance while also reducing the complexity of parameter extraction and the impact of the piecewise function′s discontinuity close to the piecewise point. The model also offers greater flexibility in dynamic threshold adjustment for various PA manufacturers. In simulation, the proposed model can reduce adjust channel power ratio from -34.1 dBc to -46.5 dBc in comparison to MP model improving 3.5 dB. Error vector magnitude performance is improved from 6.46% to 1.06%, or roughly 0.7% better than MP model. Compared to the GMP model, the complexity of parameter extraction has been reduced by 77%.

       

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