一种低复杂度的OTFS系统信号检测算法OA北大核心

For the problem of poor equalizer performance and high complexity of the linear filter in orthogonal time frequency space(OTFS)modulation systems,a signal detection algorithm for OTFS systems combining lower-upper(LU)decomposition and iterative Minimum Mean Square Error(IMMSE)equalizer(LU-IMMSE)is proposed.According to the characteristics of the sparse channel matrix in the Doppler-delay domain,a low-complexity LU decomposition method is proposed to avoid matrix inversion calculation of the MMSE equalizer.On the premise of guaranteeing the performance of the equalizer,the complexity of the equalizer is reduced.Moreover,an iterative MMSE equalizer is introduced into the OTFS systems,which approximates the optimal estimate of the MMSE equalizer by iterative updating the prior information such as the mean and variance.The proposed LU-IMMSE algorithm can effectively reduce the bit error rate(BER)by adjusting the iterative times.When the energy per bit ratio noise power spectral density is at 8 dB,the LU-IMMSE equalizer after five iterations reduces the BER by about 11 dB compared with the traditional MMSE equalizer.With the increase of iterative times,the computational complexity is reduced compared with the traditional iterative MMSE algorithm.When the maximum delay coefficient is four and the number of signs is sixteen,the proposed low-complexity LU decomposition method reduces the computational complexity of matrix inversion by about 91.72%compared with the direct inversion method.