| Autor: |
Kaleem Arshid, Zhang Jianbiao, Iftikhar Hussain, Muhammad Salman Pathan, Muhammad Yaqub, Abdul Jawad, Rizwan Munir, Fahad Ahmad |
| Jazyk: |
angličtina |
| Rok vydání: |
2022 |
| Předmět: |
|
| Zdroj: |
Egyptian Informatics Journal, Vol 23, Iss 4, Pp 77-88 (2022) |
| Druh dokumentu: |
article |
| ISSN: |
1110-8665 |
| DOI: |
10.1016/j.eij.2022.06.008 |
| Popis: |
Rapid spectrum usage in wireless networks may reduce energy efficiency, requiring cognitive radio networks to be more efficient than conventional ones. Due to increased data transmission demand, cognitive radio networks arose from a lack of spectrum bandwidth. Spectrum sensing and handoff decision are two cognitive radio network strategies that help avoid interference, channel access, and cohabitation between primary and secondary users. Current research focuses on handoff decision and cooperative spectrum sensing to improve sensing efficiency and system throughput while neglecting energy efficiency and handoff latency. Spectrum mobility and sensing are essential for energy-efficient cognitive radio networks. This study provides a second priority user transmission system using cooperative spectrum sensing to sense available channels. An energy detection technique optimizes the sensing process's energy usage, leading to energy efficiency. A primary user traffic pattern-based threshold approach is presented for spectrum mobility management. A threshold approach is utilized to calculate probabilistic stay-and-wait and QoS handoff values. The transmission channel is selected using a hybrid handoff strategy based on dynamic spectrum aggregation. Moreover, a cooperative spectrum sensing algorithm is described and simulated to identify the optimum channel with the greatest throughput and minimum energy consumption. The proposed approach increases energy efficiency and throughput while maintaining handoff delay and avoids miss-detection and false alarm. This technique improves energy efficiency, sensing performance, throughput, and handoff time. miss-detection. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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