Research Of Distributed Beamforming In The Cognitive Redio Networks

Communication technology develops rapidly with the process of the times while the demand for wireless communication is also increasing and spectrum resources shortage phenomenon is getting more obvious.To improve spectrum resource utilization is imminent.Cognitive radio technology has been a great degree of concern since it was proposed.The value of cognitive radio technology is to make the dynamic use of spectrum possible,allowing unauthorized users to share spectrum which belongs to authorized users by different spectrum sharing methods,to improve the efficiency of spectrum utilization.Relays in wireless communication can amplify and forward signals.Besides multi-node transmitting beam can be directed to obtain diversity gain.The mode of wireless communication is broadcasting,signals may be tapped by eavesdroppers which result in communication security being reduced.Secondary networks could assist primary networks to protect against being eavesdropped,while introducing additional artifacts is a common way to improve the secrecy rate.In addition,compared to the cable channel,because of the particularity of wireless communication channel,the actual situation of the channel estimation error is inevitable.Therefore research of cognitive radio network distributed beamforming has important theoretical and practical significance.The main works of this paper includes the following.Firstly,in a non-relay scenario,the system model of two secondary networks while mutual protection of each other to reduce being eavesdropped between the two secondary networks and a primary network shared spectrum is study.The optimal beamforming problem is mainly solved by the theory of convex optimization and Pareto boundary.The first method is to introduce auxiliary variables and solve the problem into a series of a standard convex optimization problem in a two-dimensional space.The second method is zero-forcing beamforming.And the third adopts the approach of Pareto-optimal parameterization in a more computationally efficient way.Simulation results show that the effect of the results of performance between optimal performance and sub-optimal solution is close.Secondly,the paper studied under the condition of imperfect channel state information maximizing the secrecy rate of primary user in cognitive relay network.The problem is solved mainly through convex optimization theory,and simplification of matrix theory and optimization of semi-definite programming.Simulation results show that the robust algorithm considering channel errors is obviously better than the algorithm without robustness.