Research On Interference Alignment In Cognitive MIMO Networks

The continuous emergence and upgrading of wireless communication services make it more difficult for the inherent spectrum resources to meet the needs of new services.For this problem,the cognitive radio technology was proposed,which has brought about tremendous changes for the use of spectrum resources.The secondary user discovers the spectrum hole through spectrum sensing,and then adjusts its parameters to access the frequency band of the primary user without impeding the communication of the primary user,so as to significantly improve the spectrum utilization.However,interference in the cognitive system is a core issue that cannot be ignored.Therefore,this thesis focuses on the research of interference alignment techniques in cognitive MIMO networks.The main research contents of the thesis are as follows:Aiming at the traditional interference alignment algorithm based on the maximum signal to interference and interference to noise ratio in cognitive MIMO networks,when transmitting multiple streams,the problem of convergence is not easy to converge with the increase of signal to noise ratio and the interference between data streams is prominent.An interference alignment algorithm is studied,which considers interference between data streams and iterative restrictions.Firstly,the secondary user system eliminates interference between the primary and secondary users independently.Secondly,when eliminating interference between primary users and secondary users,generalized Rayleigh entropy is used to calculate precoding and interference based on the maximum signal to interference and noise ratio algorithm.And during the iterative process,each iteration makes the precoding and interference suppression matrix satisfy the minimum interference power in the desired signal space.Finally,the upper limit of the secondary users' reachable degree of freedom is derived.The simulation results show that the studied algorithm improves the convergence speed and the ability to suppress interference compared with the comparison algorithm,and as the signal to noise ratio increases,the advantage of the secondary users' sum capacity also increases.Aiming at the cognitive MIMO networks with multiple pairs of primary users and multiple pairs of secondary users,due to the secondary users system independently eliminates the interference between the primary and secondary users,so that the performance of the secondary users system is not ideal,an interference alignment algorithm for trigonometric decomposition of a joint primary users and secondary users channel matrix is studied.Firstly,the channel matrixes of the primary users system and secondary users system are sorted according to the channel quality.Secondly,the channel matrix of the primary users and secondary users system after the joint sorting is decomposed into trigonometric decomposition matrix.Finally,the upper limit of the secondary users' reachable degree of freedom is derived,and using the least square error to achieve the interference alignment in the secondary users system.The simulation results show that the studied algorithm effectively improves the secondary users' upper limit of freedom and sum capacity,energy efficiency,and interference suppression capability of the primary user system and the secondary user system compared with the comparison algorithm.