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A Novel ML-2D-LUT Based Adaptive Predistorter of High Power Amplifier Using New Improved RLS Algorithm

机译:改进的RLS算法的新型基于ML-2D-LUT的大功率放大器自适应预失真器

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This paper introduces a Multilevel two dimensional Look-Up-Table (ML-2D-LUT) based adaptive predistortion (APD) technique to reduce gain distortion in the saleh modeled power amplifier (HPA). The quick initialization of the ML-2D-LUT, a new improved RLS algorithm is implemented to compensate the time-varying problem in the HPA. The proposed method distinguishes the coefficients successfully. Moreover, additional convergence in steady state and less steady state error (SSE) will be accomplished for the power amplifiers with profound impacts in the memory by using the modified step-size parameter. Simulation results demonstrate that the proposed technique offers enhanced the PA efficiency for non-constant envelope modulations and nonlinear distortions can be extraordinarily decreased with the NIRLS algorithm. The BER and MSE results conclude that the proposed technique gives better results than conventional RLS.
机译:本文介绍了一种基于多层二维查找表(ML-2D-LUT)的自适应预失真(APD)技术,以减少在萨利赫模型功率放大器(HPA)中的增益失真。 ML-2D-LUT的快速初始化是一种新的改进的RLS算法,用于补偿HPA中的时变问题。所提出的方法成功地区分了系数。此外,通过使用修改后的步长参数,将对存储器产生重大影响的功率放大器将获得稳态下的收敛性和较小的稳态误差(SSE)。仿真结果表明,所提出的技术为非恒定包络调制提供了增强的PA效率,并且使用NIRLS算法可以极大地减少非线性失真。 BER和MSE结果得出结论,与传统的RLS相比,所提出的技术给出了更好的结果。

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