In this paper, the energy-efficient power control problem in cognitive radio （CR） networks is studied not only to provide energy-efficient transmission, but also to guarantee the normal operation of primary users （...In this paper, the energy-efficient power control problem in cognitive radio （CR） networks is studied not only to provide energy-efficient transmission, but also to guarantee the normal operation of primary users （PUs）. Moreover, the static energy-efficient power control （SEPC） algorithm is proposed in static scenario to maximize the capacity of secondary users （SUs） and to reduce the power consumption according to the interference from PU to SU. Furthermore, based on the analysis of PU＇s dynamic feature with Markov chain and SEPC algorithm,the dynamic energy-efficient power control （DEPC） algorithm is proposed taking into account the probability of detection and false alarm caused by sensing errors. Extensive simulation results show that the performance of the proposed algorithms is significantly improved compared with the existing algorithm.展开更多
基金the National Natural Science Foundation of China，Beijing Municipal Natural Science Foundation，the Key Project of Ministry of Industry and Information Technology，the National Youth Science Foundation
文摘In this paper, the energy-efficient power control problem in cognitive radio （CR） networks is studied not only to provide energy-efficient transmission, but also to guarantee the normal operation of primary users （PUs）. Moreover, the static energy-efficient power control （SEPC） algorithm is proposed in static scenario to maximize the capacity of secondary users （SUs） and to reduce the power consumption according to the interference from PU to SU. Furthermore, based on the analysis of PU＇s dynamic feature with Markov chain and SEPC algorithm,the dynamic energy-efficient power control （DEPC） algorithm is proposed taking into account the probability of detection and false alarm caused by sensing errors. Extensive simulation results show that the performance of the proposed algorithms is significantly improved compared with the existing algorithm.
