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| Title | An Energy-Aware Cognitive Radio-Based Communication Approach For Next Generation Wireless Networks |
|---|---|
| ID_Doc | 8007 |
| Authors | Khaled H.; Ahmad I.; Habibi D.; Phung Q.V. |
| Year | 2019 |
| Published | Proceedings - 21st IEEE International Conference on High Performance Computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019 |
| DOI | http://dx.doi.org/10.1109/HPCC/SmartCity/DSS.2019.00250 |
| Abstract | The software-defined radio technology along with the cognitive radio technique, which aims to make the best use of available spectrum by allowing unlicensed users to opportunistically use unused bands of licensed spectrum, has strong potential to solve the looming spectrum scarcity problem in next generation wireless networks. This has motivated researchers to investigate different aspects of the cognitive radio technique including channel discovery, channel allocation, and optimum resource utilization. One major impediment which has been overlooked so far and may prove to be a sticking point is the excessive power consumption caused by power-hungry mechanisms used in cognitive radio. This is particularly critical for battery-powered devices such as smart-phones, where the excessive power consumption can easily overwhelm the benefits offered by the cognitive radio technique. In this paper, we consider the power consumption aspect of cognitive radio and introduce a new approach to maximize the potential benefit for users. The proposed approach considers the battery levels of portable devices, the nature of traffic to be sent by these devices, and the number of idle spectrum holes. We show that portable devices with battery levels less than a certain threshold experience no real benefit from the cognitive radio technique. The proposed approach can potentially open a new direction towards the development of green cognitive radio technologies. © 2019 IEEE. |
| Author Keywords | cognitive radio; energy efficiency; next generation wireless networks; software defined radio |
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