Low Complexity SLM Method Based on Threshold Classification for PAPR Reduction in OFDM Systems

被引：0

作者：

Zhou, Zhuang ^{[1
,2
]}

Wang, Lingyin ^{[1
,2
]}

Hu, Chi ^{[1
,2
]}

机构：

[1] Univ Jinan, Sch Informat Sci & Engn, Jinan 250022, Peoples R China

[2] Univ Jinan, Shandong Prov Key Lab Network Based Intelligent C, Jinan 250022, Peoples R China

来源：

FUZZY SYSTEMS AND DATA MINING V (FSDM 2019) | 2019年 / 320卷

基金：

中国国家自然科学基金;

关键词：

OFDM; PAPR; Selective Mapping; Threshold Classification; AVERAGE POWER RATIO; ALGORITHM;

D O I：

10.3233/FAIA190269

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Orthogonal frequency division multiplexing (OFDM) signal has a very high peak-to-average power ratio (PAPR), resulting in a serious decline in the performance of OFDM systems. Although original selective mapping (OSLM) can obviously reduce the PAPR of OFDM signals, it has large complexity. In order to reduce computational complexity, a low complexity SLM named threshold classification SLM (TC-SLM) has been proposed, which utilizes two orthogonal phase factor sets and threshold classification to reduce the complexity. Simulation results show that the proposed TC-SLM not only successfully achieves a reasonable PAPR performance, but also can reduce the computational complexity clearly.

引用

页码：951 / 957

页数：7

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