计算机工程与应用2016，Vol.52Issue(7)：96-100,105,6.DOI:10.3778/j.issn.1002-8331.1405-0162
基于自适应模糊神经网络的功放预失真新方法
New method of power amplifier pre-distortion based on adaptive fuzzy neural network
摘要
Abstract
To overcome the pre-distortion limitations of structure and precision for nonlinear power amplifiers with mem-ory in wireless communication system, an adaptive pre-distortion method with a dual-loop learning structure based on fuzzy neural network model identification is proposed. This method is based on real-valued time-delay fuzzy neural net-work model, and uses simplified particle swarm optimization algorithm to ensure network parameters with indirect struc-ture off-line training as the initial of the pre-distortion model. Then it uses least mean square algorithm to adjust the param-eters of pre-distorter adaptively with direct structure on-line training, and fits the nonlinearity and memory effect of power amplifier. This method has simple structure, fast convergence speed and high precision, and avoids falling into the local optimum. The results show that this scheme makes adjacent channel power ratio improve about 7 dB than the method of classic dual-loop learning structure, and improve the linearity of the power amplifier obviously. Therefore the simulation results verify the feasibility of the method.关键词
功率放大器/预失真/模糊神经网络/记忆非线性/简化粒子群优化算法Key words
power amplifier/pre-distortion/fuzzy neural network/nonlinearity with memory/simplified particle swarm optimization algorithm分类
信息技术与安全科学引用本文复制引用
南敬昌,周丹,高明明..基于自适应模糊神经网络的功放预失真新方法[J].计算机工程与应用,2016,52(7):96-100,105,6.基金项目
国家自然科学基金（No.61372058）；辽宁省高等学校优秀科技人才支持计划（No.LR2013012）；辽宁工程技术大学研究生科研资助项目（No.5B2014032）。 （）
