Application of Computational Intelligence Algorithms in Radio Propagation: A Systematic Review and Metadata Analysis

被引:10
作者
Adebowale, Quadri Ramon [1 ]
Faruk, Nasir [1 ,2 ]
Adewole, Kayode S. [3 ]
Abdulkarim, Abubakar [4 ]
Olawoyin, Lukman A. [1 ]
Oloyede, Abdulkarim A. [1 ]
Chiroma, Haruna [5 ,6 ]
Usman, Aliyu D. [7 ]
Calafate, Carlos T. [8 ]
机构
[1] Univ Ilorin, Dept Telecommun Sci, Ilorin, Nigeria
[2] Sule Lamido Univ, Dept Phys, Kano, Nigeria
[3] Univ Ilorin, Dept Comp Sci, Ilorin, Nigeria
[4] Ahmadu Bello Univ, Dept Elect Engn, Zaria, Nigeria
[5] Univ Hafr Batin, Coll Comp Sci & Engn, Hafar Al Batin, Saudi Arabia
[6] Natl Yunlin Univ Sci & Technol, Future Technol Res Ctr, Touliu, Yunlin, Taiwan
[7] Ahmadu Bello Univ, Dept Elect & Telecommun Engn, Zaria, Nigeria
[8] Univ Politecn Valencia, Dept Comp Engn, Valencia, Spain
关键词
PATH-LOSS PREDICTION;
D O I
10.1155/2021/6619364
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The importance of wireless path loss prediction and interference minimization studies in various environments cannot be over-emphasized. In fact, numerous researchers have done massive work on scrutinizing the effectiveness of existing path loss models for channel modeling. The difficulties experienced by the researchers determining or having the detailed information about the propagating environment prompted for the use of computational intelligence (CI) methods in the prediction of path loss. This paper presents a comprehensive and systematic literature review on the application of nature-inspired computational approaches in radio propagation analysis. In particular, we cover artificial neural networks (ANNs), fuzzy inference systems (FISs), swarm intelligence (SI), and other computational techniques. The main research trends and a general overview of the different research areas, open research issues, and future research directions are also presented in this paper. This review paper will serve as reference material for researchers in the field of channel modeling or radio propagation and in particular for research in path loss prediction.
引用
收藏
页数:20
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