基于并行粒子群优化算法的预失真器设计

高功率放大器是无线通信系统中非线性失真的主要来源之一. 数字基带预失真技术能有效地降低系统非线性失真,提高系统传输性能. 采用Hammerstein模型作为预失真器的模型结构,通过粒子群优化算法(particle swarm algorithm, PSO)估计预失真器系数,解决了梯度算法无法直接估计Hammerstein模型系数和易陷入局部极值等问题. 通过对PSO算法进行并行优化设计,使算法最大加速度比达3以上,加快了算法处理速度. 仿真结果表明新算法能够有效抑制系统带外频谱再生现象,减小相邻信道功率比(ACPR)达25 dB. 

Design of Predistorter Based on Parallel Particle Swarm Optimization Algorithm

High power amplifier (HPA) is one of the main sources of nonlinear distortion in wireless communication systems. Digital baseband predistortion technology can effectively reduce the nonlinear distortion and improve the system transmission performance. In this paper, a particle swarm optimization(PSO) algorithm was used directly to estimate the parameters of Hammerstein predsitorter model and to solve the local maximum problem of gradient algorithms. The predistortion algorithm was optimized into a parallel computing structure which could lead to the maximum acceleration rate of the algorithm greater than 3. Simulation results show that the proposed algorithm can effectively suppress the spectrum regrowth outside band and reduce ACPR about 25 dB.