基于SLM-PTS算法融合的NC-OFDM峰均比优化

周杰; Esono Mikue Bernardo Esono; 王学英; 周惠婷; 罗宏

doi:10.11959/j.issn.1000-0801.2022155

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基于SLM-PTS算法融合的NC-OFDM峰均比优化

研究与开发 | 更新时间：2024-06-05

- 基于SLM-PTS算法融合的NC-OFDM峰均比优化
- PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems
- 电信科学 2022年38卷第7期页码：63-74
- 作者机构：
  
  1. 南京信息工程大学电子与信息工程学院，江苏南京 210044
  2. 南京信息工程大学图书馆，江苏南京 210044
- 作者简介：
  
  [ "周杰（1964- ），男，博士，南京信息工程大学电子与信息工程学院教授、图书馆馆长，主要研究方向为无线通信、大规模MIMO等" ]
  [ "Esono Mikue Bernardo Esono（1993- ），男，南京信息工程大学电子与信息工程学院硕士生，主要研究方向为OFDM通信、OpenWrt路由器、无线 5G 模块/4G 模块/Wi-Fi 模块STM32控制板" ]
  [ "王学英（1995- ），女，南京信息工程大学电子与信息工程学院硕士生，主要研究方向为无线通信理论、信道建模" ]
  [ "周惠婷（1995- ），女，南京信息工程大学电子与信息工程学院硕士生，主要研究方向为无线通信理论、OFDM通信" ]
  [ "罗宏（1968- ），女，南京信息工程大学图书馆副研究馆员，主要研究方向为无线通信理论、信息服务与用户研究" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61971167);国家自然科学基金资助项目;The National Natural Science Foundation of China(62101275);国家自然科学基金资助项目;The National Natural Science Foundation of China(62101274);江苏省信息与通信工程优势学科建设项目
- DOI：10.11959/j.issn.1000-0801.2022155
  中图分类号： TP319
- 网络出版日期：2022-07，
  
  纸质出版日期：2022-07-20
- 稿件说明：
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周杰, Esono Mikue Bernardo Esono, 王学英, 等. 基于SLM-PTS算法融合的NC-OFDM峰均比优化[J]. 电信科学, 2022,38(7):63-74.

Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, et al. PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems[J]. Telecommunications science, 2022, 38(7): 63-74.
周杰, Esono Mikue Bernardo Esono, 王学英, 等. 基于SLM-PTS算法融合的NC-OFDM峰均比优化[J]. 电信科学, 2022,38(7):63-74. DOI： 10.11959/j.issn.1000-0801.2022155.

Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, et al. PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems[J]. Telecommunications science, 2022, 38(7): 63-74. DOI： 10.11959/j.issn.1000-0801.2022155.

摘要

基于非连续正交频分复用（non-continuous orthogonal frequency division multiplexing，NC-OFDM）模型，提出和研究了选择映射（selected mapping，SLM）算法和部分传输序列（partial transmit sequence，PTS）算法，及其SLM-PTS融合优化技术，设计了融合模型和改进流程。仿真结果与其他文献方法进行了对比，验证了SLM-PTS的融合具有优秀的峰值平均功率比（peak to average power ratio，PAPR）降低能力，但缺点是算法实现复杂度过高。因此，又进一步提出了互补型映射和限幅的联合算法（SLM-Clipping）融合解决方案，并利用深度学习方法建立PAPRnet模型。仿真结果验证了此算法对NC-OFDM系统具有PAPR良好的抑制效果，而且能够提高仿真运算效率。

Abstract

Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model

a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed

and a system model of fusion technology was designed.Through simulation comparison with other literature methods

it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability

but the algorithm implementation complexity was too high.Therefore

a complementary SLM-Clipping fusion solution was proposed

and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method

the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system

and greatly improves the computational efficiency.

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Keywords

references

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