论文标题

OTF调制的双词稀疏的MMSE涡轮均衡

Doubly-Iterative Sparsified MMSE Turbo Equalization for OTFS Modulation

论文作者

Li, Haotian, Yu, Qiyue

论文摘要

当前,正交时间频率空间(OTFS)调制引起了人们对高活动性场景中可靠通信的广泛关注。本文提出了一个双重稀疏的最小均方误差(DI-S-MMSE)涡轮均衡器,迭代地在软输入输入(SISO)MMSE估计器和SISO解码器之间迭代交换外部信息。我们提出的均衡器不会遭受短循环的影响,并且接近了近距离符号的最大符号(MAP)算法的性能。为了利用OTFS系统的固有稀疏性,我们求助于图理论,以研究通道矩阵的稀疏模式,并提出了两种稀疏指南,以减少在MMSE估计剂处计算矩阵逆的复杂性。然后,我们将两种迭代算法应用于MMSE估计,即广义最小残留(GMRE)和分解的稀疏近似逆(FSPAI)算法。前者用于最初的涡轮迭代,其全球融合在我们的均衡器中得到了证明,而后者则在我们提出的指南的帮助下在随后的涡轮迭代中使用。仿真结果表明,我们的均衡器具有复杂性的线性顺序,而稀疏期产生的性能损失仅为0.2 dB,$ 10^{ - 4} $ BIT错误率。模拟代码可用于复制本文介绍的结果:https://github.com/alga53/dismmse-turbo-equalizer-for-otfs。

Currently, orthogonal time frequency space (OTFS) modulation has drawn much attention to reliable communications in high-mobility scenarios. This paper proposes a doubly-iterative sparsified minimum mean square error (DI-S-MMSE) turbo equalizer, which iteratively exchanges the extrinsic information between a soft-input-soft-input (SISO) MMSE estimator and a SISO decoder. Our proposed equalizer does not suffer from short loops and approaches the performance of the near-optimal symbol-wise maximum a posteriori (MAP) algorithm. To exploit the inherent sparsity of OTFS system, we resort to graph theory to investigate the sparsity pattern of the channel matrix, and propose two sparsification guidelines to reduce the complexity of calculating the matrix inverse at the MMSE estimator. Then, we apply two iterative algorithms to MMSE estimation, i.e., the Generalized Minimal Residual (GMRES) and Factorized Sparse Approximate Inverse (FSPAI) algorithms. The former is used at the initial turbo iteration, whose global convergence is proven in our equalizer, while the latter is used at the subsequent turbo iterations with the help of our proposed guidelines. Simulation results demonstrate that our equalizer has a linear order of complexity while the performance loss incurred by the sparsification is only 0.2 dB at $10^{-4}$ bit error rate. Simulation codes are available to reproduce the results presented in this paper: https://github.com/Alga53/DISMMSE-Turbo-Equalizer-for-OTFS.

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