Researcn On Key Tecnnoiogies Of Resource Allocation In Spectrum-Sharing Communication Network

With the improvement of the fifth generation mobile communication network technology,the number of mobile devices with different functions is exploding.The contradiction between the user's demand for high data rates and multi-functional devices and the current limited spectrum resources and fixed spectrum allocation methods has led to an unprecedented serious problem of spectrum scarcity.As an advanced communication network,the spectrum-sharing communication network(SSCN)can utilize spectrum-sharing technique to achieve multi-user communication under limited frequency band resources,thereby improving spectrum utilization.In a SSCN,the optimal resource allocation scheme can not only improve the performance of the network,but also implements multiple communication requirements of mobile devices,and provides users with better service.Due to the limited storage energy of mobile devices,energy shortage has always restricted the performance improvement of SSCNs.In addition,due to the openness of the spectrum in the SSCN,potentially malicious users can illegally access the authorized frequency bands of legal users,leading to the leakage of confidential information.Thus,it is necessary to study the communication security in the SSCN to improve the secrecy rate of the network.On the other hand,in practice,it is difficult for the transmitter to accurately estimate the channels statement information in SSCN,and the nonrobust resource allocation lead to a serious loss of system performance.Thus,it is necessary to design a robust optimal resource allocation strategy to cope with unstable communication links,and ensure the robust performance of the SSCN.However,the existing research on SSCNs is still scarce.In this paper,to solve the problems of energy shortage,secure communication security and robust resource allocation in the SSCN,the optimal resource allocation schemes are designed in energy-harvesting SSCN,secure SSCN and robust secure SSCN,respectively.The schemes can improve the spectrum efficiency of the network,and has achieved the following research results.1.Optimal resource allocation for energy-harvesting SSCNIn order to solve energy shortage in SSCNs,the energy harvesting technology is used to charge the integrated radar-communication(IRC)transmitter in the SSCN.A"harvest-then-transmit" protocol is applied to simultaneously guarantee the detection performance of the radar and the transmission rate of communication.Aiming at the proposed energy consumption minimization problem,using positive semidefinite matrix relaxation and convex optimization theory,the optimal resource allocation strategy is proposed.The optimal beamforming,the IRC waveform,and energy-harvesting time have proposed to minimize the energy consumption of base station.Simulation results show that compared with the traditional average power allocation strategy,the proposed resource allocation strategy can guarantee the detection accuracy of the radar target and the user's communication rate with less energy consumption.2.Optimal resource allocation for secure SSCNIn order to achieve secure communication in SSCNs,a secrecy rate maximization problem is proposed in the IRC system based on the physical layer security technology.Under limited power constraints,the signal precoding matrix and artificial noise of the IRC transmitter are designed to ensure the detection accuracy of the radar target and maximize the secrecy rate of legitimate users in the presence of multiple eavesdroppers.Based on a linearization method and convex optimization theory,the paper has proposed an alternating optimization algorithm to iteratively solve the original non-convex problem.Simulation results verify the feasibility of the proposed scheme.3.Optimal resource allocation for robust secure SSCNTo address the issue of robust and secure communication in SSCNs,based on physical layer security and robust optimization technology,an average secrecy rate maximization problem is formulated in the unmanned aerial vehicle(UAV)-enabled cognitive radio networks.On the basis of ensuring the quality of service provided to the primary user,we take advantage of the high flexibility and flight controllability of the UAV to achieve secure communication of the secondary user.In this paper,we take into account two practical inaccurate location estimation cases,namely,the bounded location estimation error model and the probabilistic location estimation error model,and robustly optimize the flight trajectory and transmission power of the UAV.For the above two location estimation error models,two iterative optimization algorithms have proposed based on S-Procedure and Bernstein-type inequalities,respectively,and obtained the efficient suboptimal solution of the corresponding problem.The simulation results show that compared with the iterative algorithm achieved under the bounded location estimation error model,the iterative optimization algorithm achieved under the probabilistic location estimation error model can not only achieve a higher average secrecy rate,but also a lower computational complexity.In addition,compared with the traditional fixed trajectory schemes or non-robust optimization scheme,the two proposed robust optimization schemes can significantly improve the communication security of secondary users.