Sensing‐energy efficiency tradeoff for cognitive radio networks. Issue 18 (1st December 2014)

• Record Type: Journal Article
• Authors: Zhang, Jing; Zheng, Fu‐Chun; Gao, Xi‐Qi; Zhu, Hong‐Bo
• Is Part Of: IET communications. Volume 8:Issue 18(2014)
• Page Start: 3414
• Page End: 3423
• Publication Date: 2014-12-01
• Subjects: radio spectrum management -- telecommunication power management -- cognitive radio -- interference suppression -- mobility management (mobile radio) -- optimisation -- energy conservation; green CRN -- MAC frame -- stop‐and‐wait scheme -- throughput‐to‐power ratio -- channel handoff -- interference‐avoidance schemes -- spectrum sensing -- cognitive radio networks -- SET -- EE optimisation problem -- sensing‐energy efficiency tradeoff; Telecommunication systems -- Periodicals; Speech processing systems -- Periodicals; 621.38205
• DOI: 10.1049/iet-com.2014.0400
• Languages: English
• ISSNs: 1751-8628

Abstract

Abstract : In this study, the authors focus on the tradeoff between spectrum sensing and energy efficiency of cognitive radio networks (CRN). Considering two interference‐avoidance schemes, that is, channel handoff and stop‐and‐wait, the authors, respectively, model the energy efficiency (EE) of CRN as the mean of the throughput‐to‐power ratio. Research shows that stop‐and‐wait scheme is a special case of channel handoff from an EE perspective. Based on the proposed EE model, the authors build up an EE optimisation problem under the constraint of the sensing quality, and formulate the sensing‐energy efficiency tradeoff (SET) for CRN. The similarity and difference between the SET and the sensing‐throughput tradeoff are also investigated. Simulation analysis confirms that there is indeed an optimal sensing time to make the EE maximum, and it is larger than that for maximum throughput. Another interesting result is that the EE and the throughput of CRN can be enhanced together by optimising MAC frame structure in combination with sensing bandwidth adjustment and power control. Our work provides some insights for green CRN in view of MAC frame optimisation.