基于线性规划的基于ofdm的JRC系统PAPR最小化实用算法

IF 5.7 2区计算机科学 Q1 ENGINEERING, AEROSPACE

IEEE Transactions on Aerospace and Electronic Systems Pub Date : 2025-06-18 DOI:10.1109/TAES.2025.3580687

Prasanth Logaraman;Aakash Arora;Prabhu Babu

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引用次数: 0

摘要

基于正交频分复用（OFDM）的联合雷达通信（JRC）系统在发射信号峰值平均功率比（PAPR）较大时存在信号失真问题。这是由于功率放大器的非线性特性。PAPR最小化问题在文献中得到了很好的研究。然而，大多数算法都有很高的计算成本，使得它们不适合实时应用。为此，我们提出了一种基于线性规划（LP）的迭代降低PAPR的算法来解决这个问题。更精确地说，我们通过求解一系列LP问题来解决非凸PAPR最小化问题。该方法在较短的执行时间内显著降低了初始化波形的PAPR，并且在雷达感知和通信性能方面优于现有技术。

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A Practical PAPR Minimization Algorithm for OFDM-Based JRC Systems via Linear Programming

Orthogonal frequency-division multiplexing (OFDM)-based joint radar communication (JRC) systems have signal distortion when the transmit signal has a high peak-to-average power ratio (PAPR). This is due to the nonlinear nature of the power amplifier. The problem of PAPR minimization is well-studied in literature. However, most of the algorithms have high computational costs, making them impractical for real-time applications. To that end, we address this problem by proposing a linear programming (LP)-based algorithm that iteratively decreases the PAPR. More precisely, we solve the nonconvex PAPR minimization problem by solving a sequence of LP problems. The proposed method significantly reduces the PAPR of the initialized waveform within a short execution time and outperforms the existing techniques in terms of both radar sensing and communication performance.

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来源期刊

IEEE Transactions on Aerospace and Electronic Systems 工程技术-电信学

CiteScore

7.80

自引率

13.60%

发文量

433

审稿时长

8.7 months

期刊介绍： IEEE Transactions on Aerospace and Electronic Systems focuses on the organization, design, development, integration, and operation of complex systems for space, air, ocean, or ground environment. These systems include, but are not limited to, navigation, avionics, spacecraft, aerospace power, radar, sonar, telemetry, defense, transportation, automated testing, and command and control.