The Research Of Energy-saving Technologies In Cognitive Wireless Network With RF Energy Harvesting

Nowadays,the wireless communication has a rapid development.The users' demand for spectrum resources and energy resources has increased sharply.As a result,the green wireless communication,as a efficient technology of improving spectrum efficiency and reducing network energy consumption,is a major issue to be studied.Cognitive wireless network,which is based on cognitive radio technology,allows primary users to share the spectrum with the secondary users,thereby improving spectrum utilization.RF energy harvesting technology can harvest energy from the RF energy sources of surrounding environment and convert it into electrical energy,so as to provide energy to supply network nodes and to achieve network energy saving.The application of RF energy harvesting in cognitive wireless network is the development trend of green communications.The main study in this paper is the cognitive wireless network energy-saving technologies based on RF energy harvesting.The main contents of this paper are the following two points.1.This paper studies the dynamic management strategy of secondary users' operating modes in cognitive wireless network with RF energy harvesting.The secondary user has the ability to harvest and store RF energy,and supply for the subsequent data transmission.But the energy storage queue of the secondary user is limited.Therefore,we need dynamic management of the secondary user' operating mode,and rational as well as efficient use of the acquired RF energy.Considering the channel occupancy and channel quality information of the primary network,we propose a three-state discrete Markov channel model.On this basis,a new operating mode dynamic management strategy based on Markov Decision is proposed.According to the channel state and the available energy of the energy queen,the secondary user can decide whether to conduct RF energy harvesting or transport data packet.In this way,we can improve the RF energy efficiency,reduce unnecessary energy consumption and improve average network throughput.In this paper,we verify its performance.2.This paper combines the cognitive wireless network with RF energy harvesting and relay collaboration technology,and studies the relay selection algorithm and power allocation algorithm of the cognitive relay network.The source node and the relay node of secondary users are equipped with RF energy harvesting capability and unlimited energy storage queue.For the time-varying characteristic of the channel state information of the source node and the relay node,as well as the imbalance of the harvested RF energy and the remaining energy in the energy storage queue,this paper proposed a relay selection algorithm.This algorithm can help to select the best relay node from M relay nodes.We also proposed a power allocation algorithm based on the best relay to balance the secondary network energy,improve the throughput of the cognitive relay network.In this paper,the effectiveness of the power allocation algorithm has been verified.