• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学

• 计算机网络与信息安全 • 上一篇    下一篇

基于多目标遗传算法的LoRa参数匹配优化

王硕禾1,刘旭1,李苏晨1,张国驹2   

  1. (1.石家庄铁道大学电气与电子工程学院,河北 石家庄 050000;
    2.北京天诚同创电气有限公司,北京 102600)
  • 收稿日期:2019-08-04 修回日期:2019-10-15 出版日期:2020-03-25 发布日期:2020-03-25
  • 基金资助:

    河北省分布式能源应用创新中心资助项目(SG20182050)

LoRa parameter matching optimization
based on multi-objective genetic algorithm
 

WANG Shuo-he1,LIU Xu1,LI Su-chen1,ZHANG Guo-ju2   

  1. (1.School of Electrical and Electronic Engineering,Shijiazhuang Tiedao University,Shijiazhuang 050000;
    2.Beijing Tiancheng Tongchuang Electric Co.,Ltd.,Beijing 102600,China)

     
  • Received:2019-08-04 Revised:2019-10-15 Online:2020-03-25 Published:2020-03-25

摘要:

从工程应用角度出发,需要LoRa无线传输系统兼备系统功耗低、传输距离短、系统稳定性好的特点,优化设计匹配参数是提高LoRa传输性能的重要途径。以LoRa无线通信的能耗最低、最远传输距离最大以及系统的鲁棒性最强为优化目标,以SF、BW、CR等参数的有效取值为约束条件,采用线性加权的方法将多目标优化问题转换为单目标问题,求出最优解。仿真和实际测试结果表明,遗传算法应用于LoRa的参数匹配具有可行性和有效性。

关键词: LoRa通信, 参数优化, 遗传算法, 线性加权

Abstract:

From the perspective of engineering application, LoRa wireless transmission system is required to have the characteristics of low system power consumption, short transmission distance and good system stability. Therefore, optimizing the matching parameters in its design is the key way to improve LoRa transmission performance. In this paper, aiming to achieve the lowest energy consumption, the longest transmission distance and the strongest system robustness of the LoRa wireless communication, the effective values of parameters such as SF, BW and CR are considered as the constraint condition, and the linear weighting method is adopted to convert the multi-objective optimization problem to a single-objective problem so as to work out the optimal solution. The simulation and actual test results show that the genetic algorithm applied to LoRa parameter matching is feasible and effective.

 

 

Key words: LoRa communication, parameter optimization, genetic algorithm, linear weighting