Research On Spectrum Sharing And Power Allocation For Interference Alignment In Cognitive MOMO Network

In traditional cognitive networks,by setting the interference threshold of the primary users' system,the interference between the primary user and the cognitive user can be effectively managed.However,due to the lack of effective resource management,the interference between the multi-user will affect the channel capacity of the system.Applying the power allocation to the interference alignment algorithm of the cognitive MIMO network can further reduce the interference,improve the efficiency and improve the system capacity.Taking these as the background,aiming at improving the rate of cognitive user systems,reducing inter-user interference,and reducing computational complexity,a research is made on the multi-user diversity algorithm based on interference alignment and the power allocation algorithm among cognitive users in cognitive MIMO networks.The main research results are as follows:1 ?The MIMO interference alignment model based of complex Gaussian random channels is introduced.The system capacities of two classic interference alignment algorithms,the maximum SNR algorithm and the minimum interference leakage algorithm are compared.Due to the minimum interference leakage algorithm does not consider the effect of SNR on the algorithm,the simulation results show that at low SNR,the performance of the minimum interference leakage algorithm is better than the maximum SNR algorithm.However,as the SNR increases,the gap between the two algorithms is also shrinking.Generally,under the condition of general SNR,the performance of the maximum SNR algorithm is better than that of the minimum interference leakage algorithm.At the same time,the interference alignment model of cognitive MIMO network is introduced,and the maximum SNR algorithm of cognitive MIMO network is simulated.The system performance of cognitive MIMO network with the same number of authorized users and cognitive users is analyzed.2 ?Because of the existing iterative interference alignment algorithm could not completely eliminate the interference,and in the case of the number of iterations is limited or the number of users is more than the number of antennas,the interference may increase drastically,which has a great impact on the user's transmission performance.For this reason,the interference alignment algorithm based on multi-user diversity in secondary users' system of cognitive MIMO network is proposed.The algorithm selects the reasonable secondary users to access the primary users' system according to theinterference of the secondary users to other users and the SNR caused by the change of the users in the network.Which enables the improvements in individual user performance and system capacity performance.Compared with the algorithm without interference alignment,the algorithm reduces the interference between users.Compared with the ergodic multi-user diversity algorithm,the algorithm reduces the complexity of the algorithm by controlling the number of users.Simulation results show the superiority of the algorithm.3?In order to achieve reasonable power allocation for cognitive users without causing interference to primary user.The interference alignment scheme focus on the cognitive MIMO network of single primary user and multiple cognitive users is proposed first,then the power allocation algorithm to maximize the total cognitive users' rate and the game theory based cognitive algorithm are designed.The power allocation algorithm that maximizes the total cognitive rate of users calculates the result of cognitive network interference alignment with different percents of power for cognitive users and chooses power allocation scheme with the best performance.The power allocation algorithm of cognitive user based on game theory allocates secondary user's power by balancing signal to noise ratio of different secondary users and interference to primary users,which can reduce the transmission power and improve the energy efficiency effectively.Simulation results show that compared with traditional equal power allocation schemes,both algorithms can further enhance the cognitive user system performance.