Bibliographische Detailangaben
| Titel: |
一种低复杂度的 OTFS 系统信号检测算法. |
| Alternate Title: |
A Low Complexity Signal Detection Algorithm for OTFS Systems. |
| Autoren: |
陈发堂1, 陈甲杰1 915346332@qq.com, 夏麒煜1, 黄梁1 |
| Quelle: |
Telecommunication Engineering. 2/28/2025, Vol. 65 Issue 2, p205-213. 9p. |
| Schlagwörter: |
DETECTION algorithms, BIT error rate, MATRIX inversion, DECOMPOSITION method, SIGNAL detection |
| Abstract (English): |
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 Dopplerdelay 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. [ABSTRACT FROM AUTHOR] |
| Abstract (Chinese): |
针对正交时频空(Orthogonal Time Frequency Space, OTFS)调制系统中均衡器性能不佳及线 性滤波器复杂度较高等问题, 提出了一种 LU( Lower-Upper) 分解与迭代最小均方误差( Iterative Minimum Mean Square Error, IMMSE)均衡器结合的 OTFS 系统信号检测算法(LU-IMMSE)。 该算法 依据时延多普勒域稀疏信道矩阵的特征, 采用一种低复杂度的 LU 分解方法, 以避免 MMSE 均衡器 求解矩阵逆的过程, 在保证均衡器性能的前提下降低了均衡器复杂度。 在 OTFS 系统中引入一种 IMMSE 均衡器, 通过不断迭代更新发送符号均值和方差这些先验信息来逼近 MMSE 均衡器最优估 计值。 LU-IMMSE 算法通过调节迭代次数可以有效降低误比特率。 在比特信噪比为 8 dB 时, 5 次迭 代后的 LU-IMMSE 均衡器误比特率相比传统的 MMSE 均衡器降低了约 11 dB。 随着迭代次数的增 大, 较传统 IMMSE 算法降低了计算复杂度。 在最大时延系数为 4、符号数为 16 的情况下, 与直接求 逆相比, 所提出的低复杂度 LU 分解方法降低了约 91. 72% 的矩阵求逆计算复杂度。 [ABSTRACT FROM AUTHOR] |
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