A PAPR Reduction Method Based on Artificial Bee Colony Algorithm for OFDM Signals

OFDM系统中深度联合信源信道编码的PAPR降低技术综合研究

A Comprehensive Study of PAPR Reduction Techniques for Deep Joint Source Channel Coding in OFDM Systems

本文系统研究了OFDM系统中深度联合信源信道编码的PAPR降低技术，对比传统方法与深度学习方法，发现带重训练的限幅在失真类技术中性能最优，而非失真类技术可在不损害重建质量的前提下有效降低PAPR。

An improved bearing fault detection strategy based on artificial bee colony algorithm

The operating state of bearing directly affects the performance of rotating machinery and how to accurately and decisively extract features from the original vibration signal and recognize the faulty parts as early as possible is very critical. In this study, the one-dimensional ternary model which has been proved to be an effective statistical method in feature selection is introduced and shapelets transformation is proposed to calculate the parameter of it which is also the standard deviation of the transformed shaplets that is usually selected by trial and error. Moreover, XGBoost is used t…

ISAC系统中广义OFDM波形集的PAPR与模糊函数之间的最优权衡

The Optimal Tradeoff Between PAPR and Ambiguity Functions for Generalized OFDM Waveform Set in ISAC Systems

本文针对ISAC系统，提出广义OFDM波形集，推导PAPR与自/互模糊函数的最优帕累托权衡（联合界），并设计联合优化框架，显著优于5G波形。

SWAN: Swarm-Based Low-Complexity Scheme for PAPR Reduction

Cyclically shifted partial transmit sequences (CS-PTS) has conventionally been used in SISO systems for PAPR reduction of OFDM signals. Compared to other techniques, CS-PTS attains superior performance. Nevertheless, due to the exhaustive search requirement, it demands excessive computational complexity. In this paper, we adapt CS-PTS to operate in a MIMO framework, where singular value decomposition (SVD) precoding is employed. We also propose SWAN, a novel optimization method based on swarm intelligence to circumvent the exhaustive search. SWAN not only provides a significant reduction in co…

Semantic Communications with Discrete-time Analog Transmission: A PAPR Perspective

Recent progress in deep learning (DL)-based joint source-channel coding (DeepJSCC) has led to a new paradigm of semantic communications. Two salient features of DeepJSCC-based semantic communications are the exploitation of semantic-aware features directly from the source signal, and the discrete-time analog transmission (DTAT) of these features. Compared with traditional digital communications, semantic communications with DeepJSCC provide superior reconstruction performance at the receiver and graceful degradation with diminishing channel quality, but also exhibit a large peak-to-average pow…

Multi-objective design of multilayer microwave dielectric filters using artificial bee colony algorithm

Artificial bee colony algorithm (ABC) developed by inspiring the foraging phenomena of the natural honey bees is a simple and powerful metaheuristic optimization algorithm. The performance of single objective ABC performance has been well demonstrated by implemented to different design optimization problems from elec-trical and mechanical to civil engineering. Its efficacy is anticipated in the multi-objective design optimization of multilayer microwave dielectric filters (MMDFs) which is a challenging multi-objective problem falls into the context of electromagnetic (EM) design in electrical …