基于独立分量分析的盲解码接收算法

Blind Decoding and Receiving Algorithm Based on Independent Component Analysis

为了解决广义频分复用(generalized frequency division multiplex,GFDM)系统接入信号中现有快速傅里叶变换(fast Fourier transform,FFT)解码算法需要先进行同步的缺点,通过独立分量方法研究了异步情况下基于独立分量分析(independent component analysis,ICA)的解码算法。该算法可以在未知传输延时和载波偏移的非同步情况下,对多用户GFDM系统信号进行盲分离和解码,降低了定时和频偏估计误差对解码性能的影响,同时不需要去除循环前缀,增加了接收信号的能量,提高了解码性能。理论分析和仿真结果表明:在平稳信道环境下,随着循环前缀的长度增加,基于ICA的解码算法相比于传统的FFT解码算法至少获得约2 dB的性能增益。

In order to solve the problem that the existing fast fourier transform(FFT)decoding algorithm in the access signal of the generalized frequency division multiplex(GFDM)system needs to synchronize firstly,the independent component analysis method was used to study the decoding algorithm based on independent component analysis(ICA)under asynchronous conditions.The algorithm can blind separate and decode the signals of multi-user GFDM system under the asynchronous situation of unknown transmission delay and carrier offset,reducing the impact of timing and frequency offset estimation errors on decoding performance.At the same time,it doesn't need to remove the cyclic prefix,and increases the energy of the received signal,and improves the decoding performance.Theoretical analysis and simulation results show that in a stable channel environment,as the length of the cyclic prefix increases,the ICA-based decoding algorithm can obtain at least a performance gain of about 2 dB compared with the traditional FFT decoding algorithm.