关键词: 认知无线电网络, 接入控制, 发射功率波束形成, 增广Lagrange函数, Armijo梯度下降法

Abstract: In cognitive radio networks, for the robust joint optimization problem of multiuser admission control and power beamforming, a joint optimization scheme based on smooth approximation of entropy function was proposed. Firstly, the two optimization problems of admission control and transmit power beams were converted into a joint optimization problem by L₀-norm minimization. Secondly, the method of smoothing approximation based on entropy function was used to optimize the non-convexity and discontinuity of L₀-norm. Finally, since the objective function was smooth, differentiable and unimodal function, the problem was transformed into the Lagrange function, and Armijo gradient descent method was used to get the optimal solution. The numerical results show that by using the proposed algorithm, the number of admitted uses is not significantly increased when the Signal-to-Interference-plus-Noise Ratio (SINR) is relatively low, but the transmission power consumption is decreased and the number of admitted uses is increased when SINR is relatively high. The uncertain Channel State Information (CSI) of model is analyzed, which can make the network better adapt to the changes of the outside world and improve the reliability of the network. The proposed algorithm can effectively realize the optimal allocation of the network resources and improve the network performance.

Key words: cognitive radio network, admission control, transmission power beamforming, augmented Lagrange function, Armijo gradient descent method