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—Recent works have validated the possibility of energy efficiency improvement in radio access networks (RAN), depending on dynamically turn on/off some base stations (BSs). In this paper, we extend the research over BS switching operation, matching up with traffic load variations. However, instead of depending on the predicted traffic loads, which is still(More)
—In this letter, we consider a large-scale multiple-input multiple-output (MIMO) system where the receiver should harvest energy from the transmitter by wireless power transfer to support its wireless information transmission. The energy beamforming in the large-scale MIMO system is utilized to address the challenging problem of long-distance wireless power(More)
As wireless communications experience exponential growth, energy consumption has became a crucial problem in the wireless industry. Energy efficiency of wireless systems has to be significantly improved in order to guarantee the sustainable growth of the wireless industry. Plenty of efforts have been carried on to achieve so called green wireless world. In(More)
As the scarce spectrum resource is becoming overcrowded, cognitive radio indicates great flexibility to improve the spectrum efficiency by opportunistically accessing the authorized frequency bands. One of the critical challenges for operating such radios in a network is how to efficiently allocate transmission powers and frequency resource among the(More)
Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs). In this paper, we extend the research over BS switching operations, which should match up with traffic load variations. Instead of depending on the dynamic traffic loads which are still(More)
This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication. Abstract—This paper first provides a brief survey on existing traffic offloading techniques in wireless networks. Particularly as a case study, we put forwards an on-line reinforcement learning(More)
—One of the critical challenges for secondary use of licensed spectrum is the accurate modeling of primary users' (PUs') stochastic behaviors. However, the conventional hidden Markov models (HMMs) assume stationary state transition probability and fail to adequately describe PUs' dwell time distributions. In this letter, we propose a non-stationary hidden(More)