Adaptive Hammerstein Predistorter Using the Recursive Prediction Error Method

The digital baseband predistorter is an effective technique to compensate for the nonlinearity of power amplifiers （PAs） with memory effects. However, most available adaptive predistorters based on direct learning architectures suffer from slow convergence speeds. In this paper, the recursive prediction error method is used to construct an adaptive Hammerstein predistorter based on the direct learning architecture, which is used to linearize the Wiener PA model. The effectiveness of the scheme is demonstrated on a digital video broadcasting-terrestrial system. Simulation results show that the predistorter outperforms previous predistorters based on direct learning architectures in terms of convergence speed and linearization. A similar algorithm can be applied to estimate the Wiener PA model, which will achieve high model accuracy.     

云南省自动气象站监控系统的设计与实现

主要介绍了云南省自动气象站监控系统,首先分析了建设现状和系统需求,然后对系统设计和功能的实现做了适当介绍,最后对运行情况进行简明小结.     

延时估计误差对间接学习结构预失真器的影响

间接学习结构数字基带预失真器的实现需要估计模拟链路延时,而链路延时估计算法存在估计误差,此误差对预失真器性能的影响目前未有相关研究。该文以邻近信道功率比(ACPR)和归一化均方误差(NM SE)两项指标作为衡量标准,研究了延时估计误差对间接学习结构预失真器补偿性能的影响。结果表明,间接学习结构预失真器对延时估计误差敏感,在N yqu ist采样的预失真器系统中,只有当估计误差不超过系统采样间隔的1/64时,才能保证此预失真器能够有效地实现功放线性化。