| 摘要: |
| 针对正交频分复用(Orthogonal Frequency Division Multiplexing,OFDM)系统中传统信道估计算法复杂度高或估计精度低的问题，给出一种基于反向传播(Back Propagation,BP)神经网络的信道估计方法。采用Simulink仿真工具构建OFDM信号采集平台，建立了基于BP神经网络的OFDM系统信道估计模型，并以均方误差和误码率为主要评价指标，分析了不同网络参数和导频数量对信道估计性能的影响。仿真结果表明，与传统信道估计算法相比，基于BP神经网络的信道估计算法可以提供更优的系统性能，而且可以减少导频数量，提高频带利用率。 |
| 关键词: OFDM系统 信道估计 BP神经网络 |
| DOI： |
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| 基金项目:国家自然科学基金资助项目(61871176)；河南省高等学校重点科研项目应用研究计划(19A510011)；河南工业大学科学研究基金（省属高校基本科研业务费专项资金）自然科学领域项目（2018RCJH18）;河南工业大学创新基金重点项目(2020ZKCJ02) |
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| Channel estimation of OFDM systems based on BP neural network |
| JI Qinwen,ZHU Chunhua |
| (1.Key Laboratory of Grain Information Processing and Control,Zhengzhou 450001,China;2.School of Information Science and Engineering,Henan University of Technology,Zhengzhou 450001,China;3.Henan Key Laboratory of Grain Photoelectric Detection and Control,Henan University of Technology,Zhengzhou 450001,China) |
| Abstract: |
| In order to improve the high complexity or low estimation accuracy of traditional channel estimation algorithms in orthogonal frequency division multiplexing(OFDM) systems,a channel estimation method based on back propagation(BP) neural network is proposed.The OFDM signal acquisition platform is built by Simulink,and channel estimation model based on BP neural network for the OFDM system is established.Then the influence of different network parameters and pilot number on channel estimation performance is analyzed under the main evaluation indexes of mean square error(MSE) and bit error rate(BER).The simulation results show that,compared with the traditional channel estimation algorithm,the channel estimation method based on BP neural network can not only provide better system performance,but also reduce number of pilots and improve spectral utilization. |
| Key words: OFDM system channel estimation BP neural network |
