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Srivastava V, Singh P, Malik PK, Singh R, Tanwar S, Alqahtani F, Tolba A, Marina V, Raboaca MS. Innovative Spectrum Handoff Process Using a Machine Learning-Based Metaheuristic Algorithm. SENSORS (BASEL, SWITZERLAND) 2023; 23:2011. [PMID: 36850606 PMCID: PMC9962354 DOI: 10.3390/s23042011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 01/28/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
A cognitive radio network (CRN) is an intelligent network that can detect unoccupied spectrum space without interfering with the primary user (PU). Spectrum scarcity arises due to the stable channel allocation, which the CRN handles. Spectrum handoff management is a critical problem that must be addressed in the CRN to ensure indefinite connection and profitable use of unallocated spectrum space for secondary users (SUs). Spectrum handoff (SHO) has some disadvantages, i.e., communication delay and power consumption. To overcome these drawbacks, a reduction in handoff should be a priority. This study proposes the use of dynamic spectrum access (DSA) to check for available channels for SU during handoff using a metaheuristic algorithm depending on machine learning. The simulation results show that the proposed "support vector machine-based red deer algorithm" (SVM-RDA) is resilient and has low complexity. The suggested algorithm's experimental setup offers several handoffs, unsuccessful handoffs, handoff delay, throughput, signal-to-noise ratio (SNR), SU bandwidth, and total spectrum bandwidth. This study provides an improved system performance during SHO. The inferred technique anticipates handoff delay and minimizes the handoff numbers. The results show that the recommended method is better at making predictions with fewer handoffs compared to the other three.
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Affiliation(s)
- Vikas Srivastava
- School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara 144411, India
- Department of Electronics and Communication Engineering, Pranveer Singh Institute of Technology, Kanpur 208001, India
| | - Parulpreet Singh
- School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara 144411, India
| | - Praveen Kumar Malik
- School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara 144411, India
| | - Rajesh Singh
- Division of Research and Innovation, Uttaranchal University, Dehradun 248007, India
| | - Sudeep Tanwar
- Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad 382481, India
| | - Fayez Alqahtani
- Software Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh 12372, Saudi Arabia
| | - Amr Tolba
- Computer Science Department, Community College, King Saud University, Riyadh 11437, Saudi Arabia
| | - Verdes Marina
- Department of Building Services, Faculty of Civil Engineering and Building Services, Technical University of Gheorghe Asachi, 700050 Iași, Romania
| | - Maria Simona Raboaca
- Doctoral School, University Politehnica of Bucharest, Splaiul Independentei Street No. 313, 060042 Bucharest, Romania
- National Research and Development Institute for Cryogenic and Isotopic Technologies—ICSI Rm. Vâlcea, Uzinei Street, No. 4, 240050 Râmnicu Vâlcea, Romania
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