| Compared with traditional wireless networks,energy harvesting-based cognitive radio network(EH-CRN)has significant advantages.First,it can effectively alleviate the lack of spectrum and improve spectrum utilization by multiplexing the licensed spectrum.Second,powering nodes through energy harvesting technology not only alleviates energy shortage,but also overcomes difficulties such as the inconvenience of replacing batteries or powering nodes through cables.Finally,by arranging access points on the ground or in the air,EH-CRN can be laid out quickly and flexibly.Therefore,EH-CRN can realize high-frequency and energyefficient communication anytime and anywhere,which will play an essential role in the future wireless network.However,in EH-CRN,efficient communication resource allocation schemes have become a hot research topic due to the discontinuity,randomness,and fluctuation of the energy resources available to secondary users.Therefore,this dissertation makes a profound study on the resource allocation method to maximize the spectrum efficiency and energy efficiency of EH-CRN under the complex constraints of energy,quality of service,transmit power,co-channel interference,and inter-area interference.The main research contents and contributions of this dissertation are as follows:1.The resource allocation for throughput maximization based on energy harvesting balance is studied.An energy harvesting model based on time-domain scheduling is proposed to ensure that the secondary users far away from the energy source can harvest sufficient energy.By considering the constraints of energy,interference,and the minimum rate of the secondary users,a joint resource allocation algorithm that maximizes throughput is proposed.First,the coupling of time and power optimization factors is eliminated by introducing additional variables.Then,the original problem is transformed into its Lagrangian dual problem.Finally,the optimal solution to the dual problem is obtained using the Rambling W function.The simulation results show that the complexity of the proposed algorithm is slight and can help the system to obtain better throughput performance.2.The optimal allocation of energy efficiency resources for multi-user spectrum sharing is studied.To address the spectrum "hole" problem caused by secondary user multiplexing licensed spectrum,a scheme of multiple secondary users sharing authorized spectrum simultaneously is adopted.By considering constraints such as the energy of secondary users,minimum rate,and interference power,a resource allocation algorithm to maximize energy efficiency is proposed.First,the original fractional programming is converted into a nonfractional form.Then,the Frank-Wolfe method is introduced to solve the power optimization.Finally,the harvesting time is optimized using linear programming.The simulation results verify the performance of the proposed algorithm and give the impact of different parameters on the system’s energy efficiency,which provides a reference basis for resource allocation in the scenario of multiple users sharing a single spectrum.3.The optimal resource allocation for end-to-end energy efficiency maximization is studied.To address the fading problem caused by non-line-of-sight links in terrestrial CRN,UAVs are used as access points and relays.By jointly considering energy,power,access point location,and inter-cell interference constraints,a resource allocation algorithm is proposed to maximize the end-to-end energy efficiency.First,the original fractional programming problem is transformed into a non-fractional form.Then,the optimal access point location is obtained by a circular random search strategy.Finally,the user association is solved by one-dimensional linear programming as well as power control by convex approximation methods.The simulation results show that the proposed algorithm can converge quickly and obtain the approximate optimal resource allocation solution.Moreover,the proposed algorithm can achieve better end-to-end energy efficiency gains for CRN than that using the benchmark solution.4.The optimal resource allocation for outage energy efficiency maximization is studied.To address the problem that the spectrum sensing performance of terrestrial secondary user is easily affected by obstacle occlusion,a UAV is laid out to perform spectrum sensing as an airborne secondary user.Under the constraints of the secondary user’s mean energy,outage rate,average transmit power,and interference power,a resource allocation algorithm is proposed to maximize outage energy efficiency.First,the original fractional programming problem is converted into a non-fractional one.Then,the optimal power allocation is obtained using the sub-problem partitioning method as well as the optimal sensing time by linear programming.The simulation results show that by setting an appropriate outage rate constraint value,the system can obtain energy-efficient transmission while ensuring user data’s real-time transmission requirements.In summary,this dissertation thoroughly investigates the problem of optimal resource allocation in EH-CRN,and verifies the performance of the proposed algorithm through simulation to provide a theoretical reference for the specific application of EH-CRN. |
