Improved Random Forest Algorithm for Cognitive Radio Networks' Distributed Channel and Resource Allocation Performance
- Title
- Improved Random Forest Algorithm for Cognitive Radio Networks' Distributed Channel and Resource Allocation Performance
- Creator
- Rajesh Kanna R.; Mohana Priya T.; Rohini V.; Ashok Immanuel V.; Senthilnathan T.; Kirubanand V.B.; Ibrahim A.
- Description
- Modified Random Forest (MRF) machine learning algorithm aimed at improving the distributed channel allocation and resource allocation performance in cognitive radio networks (CRNs). The purpose of this research is to enhance the efficiency and effectiveness of CRNs by optimizing the allocation of channels and resources. The proposed MRF algorithm is developed by adapting and modifying the random forest technique to address the specific challenges of CRN allocation. Experimental evaluations demonstrate that the MRF algorithm achieves higher accuracy and efficiency compared to existing routing techniques and channel allocation algorithms like ACO and PSO. It exhibits a high packet delivery ratio, increased throughput, and reduced delay in channel selection, thus improving the overall performance of CRNs.The implications of this research are twofold. On a theoretical level, this study contributes to the field by extending the capabilities of the random forest algorithm and adapting it to the domain of CRNs. The modified algorithm demonstrates the potential of machine learning techniques in addressing allocation challenges in wireless communication systems. The findings emphasize the importance of advanced algorithms in improving the efficiency and effectiveness of channel and resource allocation processes. 2023, Success Culture Press. All rights reserved.
- Source
- Journal of Logistics, Informatics and Service Science, Vol-10, No. 3, pp. 98-106.
- Date
- 2023-01-01
- Publisher
- Success Culture Press
- Subject
- Channel Allocation; Cognitive Radio Networks; Random Forest; Routing; Throughput
- Coverage
- Rajesh Kanna R., Christ (Deemed to be University), India; Mohana Priya T., Christ (Deemed to be University), India; Rohini V., Christ (Deemed to be University), India; Ashok Immanuel V., Christ (Deemed to be University), India; Senthilnathan T., Christ (Deemed to be University), India; Kirubanand V.B., Christ (Deemed to be University), India; Ibrahim A., Department of Computer Science, College of Computer, Qassim University, Buraydah, Saudi Arabia
- Rights
- All Open Access; Gold Open Access
- Relation
- ISSN: 24092665
- Format
- Online
- Language
- English
- Type
- Article
Collection
Citation
Rajesh Kanna R.; Mohana Priya T.; Rohini V.; Ashok Immanuel V.; Senthilnathan T.; Kirubanand V.B.; Ibrahim A., “Improved Random Forest Algorithm for Cognitive Radio Networks' Distributed Channel and Resource Allocation Performance,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 26, 2025, https://archives.christuniversity.in/items/show/14535.