This paper focuses on the energy efficiency of cognitive relay （CR） networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio （SNR） is studied to maximize the energy e...This paper focuses on the energy efficiency of cognitive relay （CR） networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio （SNR） is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.展开更多
基金supported by the National Science Fund under Grant No. 6087215the Yunnan Research Program of Application Foundation under Grant No.2011FB035the School training fund under granted No.KKZ3201403010
文摘This paper focuses on the energy efficiency of cognitive relay （CR） networks with cooperative sensing, joint optimization of the sensing time and the signal-to-noise ratio （SNR） is studied to maximize the energy efficiency of CR network. Theoretical analysis shows that there exists an optimal sensing time and optimal SNR to make the energy efficiency maximized under a constraint of detection probability. Simulation results illustrate that the optimal fusion rule performs better than the OR rule and the AND rule in terms of the energy efficiency. By properly designing the fusion rule threshold as well as the number of cooperative sensing users, the energy efficiency of CR networks can be further improved.
