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- Title
基于烟花爆炸式混合蛙跳算法的LoRa 网络参数分配策略.
- Authors
周 超; 章 辉; 杨茂恒; 郑天宇; 姜美君
- Abstract
In order to improve the interference and conflict problem in the LoRa transmission process, a LoRa network parameter allocation strategy based on a firework explosive shuffled frog leaping algorithm is proposed. First of all, to address the shortcomings that the shuffled frog leaping algorithm is easy to mature and be falling into local optimality, the allocation method is changed, and reverse learning, adaptive firework explosion mechanism and Gaussian mutation operator are introduced to improve the search performance of the algorithm. Secondly, maximizing the average node transmission success rate is set as the optimization target, and the receiving sensitivity is used as the constraint coefficient to allocate the best parameters under the premise that the information can be received. The simulation results show that the allocation strategy based on the firework explosive shuffled frog leaping algorithm is better than other schemes, which can significantly reduce the probability of node collision and increase the rate of node information extraction.
- Subjects
DATA mining; SEARCH algorithms; RATE setting; FIREWORKS; FROGS
- Publication
Telecommunication Engineering, 2022, Vol 62, Issue 6, p795
- ISSN
1001-893X
- Publication type
Article
- DOI
10.3969/j.issn.1001-893x.2022.06.016