基于流形优化的音调预留技术在OFDM-ISAC系统中的PAPR降低
Tone Reservation-Based PAPR Reduction Using Manifold Optimization for OFDM-ISAC Systems
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中文总结 AI 辅助
本文提出一种基于流形优化的音调预留方法，通过迭代投影梯度下降算法降低OFDM-ISAC系统的PAPR，在保持与现有技术相近的PAPR降低水平的同时，显著降低了计算复杂度并提升了感知性能。
中文摘要 AI 辅助
我们考虑在感知使能约束下，利用音调预留(TR)降低正交频分复用(OFDM)系统峰均功率比(PAPR)的挑战，使得放置在预留音调(RTs)中的信号能够被集成感知与通信(ISAC)利用。为此，该问题首先被转化为一个无约束流形优化问题，然后通过一种由无穷范数近似辅助的迭代投影梯度下降算法求解。仿真结果表明，所提方法在保持与现有技术(SotA)相似的PAPR降低水平的同时，不仅计算复杂度更低，而且在感知性能方面优于其他替代方案。
英文摘要
We consider the peak-to-average power ratio (PAPR) reduction challenge of orthogonal frequency division multiplexing (OFDM) systems utilizing tone reservation (TR) under a sensing-enabling constraint, such that the signals placed in the reserved tones (RTs) can be exploited for Integrated Sensing and Communication (ISAC). To that end, the problem is first cast as an unconstrained manifold optimization problem, and then solved via an iterative projected gradient descent algorithm assisted by an approximation of the infinity norm. Simulation results show that the proposed method, while maintaining a level of PAPR reduction similar to state of the art (SotA), not only has lower computational complexity but also outperforms the alternatives in terms of sensing performance.
