高数据速率多载波三维指数调制正交混沌移键控系统的设计与性能分析

IF 2.9 3区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Digital Signal Processing Pub Date : 2025-07-01 DOI:10.1016/j.dsp.2025.105429

Lifang He, Yanan Hu, Xibiao Chen

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引用次数: 0

摘要

提出了一种利用联合时隙、码和能量指数调制（JTCE-IM-QCSK）实现高速数据传输的多载波正交混沌移位键控通信方案。根据时隙的激活状态选择混沌信号，利用码索引生成的离散余弦变换（DCT）码对混沌信号进行扩展，显著提高了数据传输速率。此外，本文通过采用能量分配策略来提高信号能量以及噪声抑制模块来提高误码率（BER）性能。给出了系统在加性高斯白噪声（AWGN）和多径瑞利衰落信道下的误码率的理论表达式，并与其他混沌通信系统进行了数据速率、频谱效率和复杂度性能的比较。最后，通过蒙特卡罗仿真结果验证了所提方案的性能优势。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Design and performance analysis of high-data-rate multi-carrier three-dimensional index modulation quadrature chaos shift keying system

This paper proposes a novel multi-carrier quadrature chaos shift keying communication scheme that utilizes joint time slot, code, and energy index modulation (JTCE-IM-QCSK) to achieve high-speed data transmission. By selecting chaotic signals based on the activation status of time slots and expanding them using Discrete Cosine Transform (DCT) code generated by code index, the data transmission rate is significantly increased. Additionally, the paper improves the bit error rate (BER) performance by employing an energy allocation strategy to boost signal energy, along with a noise suppression module. The paper provides theoretical expressions for the system's BER under additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels, and compares its data rate, spectral efficiency, and complexity performance with other chaotic communication systems. Finally, the performance advantages of the proposed scheme are verified through Monte Carlo simulation results.

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来源期刊

Digital Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

17.20%

发文量

435

审稿时长

66 days

期刊介绍： Digital Signal Processing: A Review Journal is one of the oldest and most established journals in the field of signal processing yet it aims to be the most innovative. The Journal invites top quality research articles at the frontiers of research in all aspects of signal processing. Our objective is to provide a platform for the publication of ground-breaking research in signal processing with both academic and industrial appeal. The journal has a special emphasis on statistical signal processing methodology such as Bayesian signal processing, and encourages articles on emerging applications of signal processing such as: • big data• machine learning• internet of things• information security• systems biology and computational biology,• financial time series analysis,• autonomous vehicles,• quantum computing,• neuromorphic engineering,• human-computer interaction and intelligent user interfaces,• environmental signal processing,• geophysical signal processing including seismic signal processing,• chemioinformatics and bioinformatics,• audio, visual and performance arts,• disaster management and prevention,• renewable energy,