Resource Allocation In Wireless Powered Cognitive Radio Networks Based On A Practical Non-linear Energy Harvesting Model

With the development of the fourth generation mobile communication,the key techniques and standards for the fifth generation mobile communication systems are investigated in various countries.It is envisioned that two fundamental problems(spectrum scarcity、energy scarcity)and the basic challenges of massive users access requirement and low power consumption with high energy efficiency will be encountered by the fifth generation wireless communications networks.In this paper,resource allocation strategies are designed to maximize the sum throughput of the secondary users in wireless powered cognitive radio networks and improve energy conversation efficiency in NOMA cognitive powered networks.It is the first time to formulate the optimal resource allocation problem in wideband CWPCN under the practical non-linear EH model.Using convex theory,the energy harvesting time,channel allocation and transmit power are jointly optimized.The closed-form expressions for the optimal transmit power and channel allocation are given.Simulation results show that there is a tradeoff between the harvesting energy and the sum throughput of the secondary users.It is shown that the performance achieved under the linear energy harvesting model may be better than that achieved under the practical nonlinear energy harvesting modelA practical non-linear energy harvesting model is first applied in NOMA cognitive powered network.The framework for maximizing the harvesting energy is formulated.Using the nonlinear fractional programming and convex theories,an optimal power allocation strategy is designed.It is shown that the performance achieved under the practical nonlinear energy harvesting model is better than that achieved under the linear energy harvesting model.