A Modified Interference Channel Learning Algorithm in Cognitive MIMO System

A modified algorithm was proposed for Cognitive MIMO Secondary User to learn the interference channel to Primary User. The algorithm estimated the null space of interference channel matrix with cyclic Jacobi method, of which the parameters were acquired by binary search utilizing the power control scheme between Primary Users. Furthermore, aimed at suppressing the interference of Cognitive User to Primary User, a method of dynamically adjusting the binary search accuracy in learning was proposed to improve the convergence performance of the algorithm. Theoretical analysis and simulation results indicate that convergence rate of proposed algorithm is accelerated comparing with BNSL algorithm and interference to Primary User when performing channel learning is significantly improved.