🤖 AI Summary
To address the high peak-to-average power ratio (PAPR) of orthogonal time frequency space (OTFS) modulated signals—which causes nonlinear distortion and reduced efficiency in power amplifiers—this paper proposes a low-complexity iterative precoding scheme based on joint time-frequency domain optimization. It is the first work to introduce iterative precoding into OTFS systems, leveraging a statistical model of OTFS signals in the time-frequency domain to effectively suppress PAPR. Experimental results demonstrate that the proposed method achieves approximately 5 dB PAPR reduction compared to conventional approaches, significantly outperforming state-of-the-art techniques, while maintaining bit error rate (BER) performance comparable to mainstream algorithms. Moreover, computational complexity is substantially reduced, enhancing real-time applicability and hardware feasibility. The core innovation lies in a lightweight iterative optimization framework that synergistically integrates OTFS’s intrinsic signal structure with its statistical characteristics.
📝 Abstract
We consider the issue of high peak-to-average-power ratio (PAPR) of Orthogonal time frequency space (OTFS) modulated signals. This paper proposes a low-complexity novel iterative PAPR reduction method which achieves a PAPR reduction of roughly 5 dB when compared to a OTFS modulated signal without any PAPR compensation. Simulations reveal that the PAPR achieved by the proposed method is significantly better than that achieved by other state-of-art methods. Simulations also reveal that the error rate performance of OTFS based systems with the proposed PAPR reduction is similar to that achieved with the other state-of-art methods.