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<p>Orthogonal time frequency space (OTFS) systems have become recognized for their superior capacity to deliver high data throughput while efficiently utilizing diversity, as opposed to traditional orthogonal frequency division multiplexing. However, the complex transformation between the delay-Doppler and time domains poses a significant challenge in detecting OTFS signals. This paper proposes a novel non-stationary iteration-based approximate inversion (NSIAI) technique to address the detection challenges in uplink OTFS systems. The NSIAI approach, which has a computational complexity that scales quadratically, achieves performance levels comparable to those of a linear minimum mean square error detector. The results of the simulation show that the NSIAI approach performs better computationally than other detection methods and offers good error performance. Furthermore, the NSIAI approach exhibits robustness in the presence of imperfect channel state information at the receiver, improving its applicability in real-world scenarios.</p>

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Signal Detection in OTFS with Non-stationary Iteration Based Approximate Inversion

  • 期刊论文

  • 发表日期：

    2025年4月1日

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  • Chandan Kumar,
  • Himanshu B. Mishra,
  • Debjani Mitra

摘要

Orthogonal time frequency space (OTFS) systems have become recognized for their superior capacity to deliver high data throughput while efficiently utilizing diversity, as opposed to traditional orthogonal frequency division multiplexing. However, the complex transformation between the delay-Doppler and time domains poses a significant challenge in detecting OTFS signals. This paper proposes a novel non-stationary iteration-based approximate inversion (NSIAI) technique to address the detection challenges in uplink OTFS systems. The NSIAI approach, which has a computational complexity that scales quadratically, achieves performance levels comparable to those of a linear minimum mean square error detector. The results of the simulation show that the NSIAI approach performs better computationally than other detection methods and offers good error performance. Furthermore, the NSIAI approach exhibits robustness in the presence of imperfect channel state information at the receiver, improving its applicability in real-world scenarios.