干扰条件下的星空协作认知网络鲁棒波束成形算法

Robust Beamforming Algorithm for Cognitive Satellite and Aerial Cooperative Networks with Interference

针对无人机(Unmanned Aerial Vehicle,UAV)作为中继站辅助卫星通信构成的星空协作网络,提出了一种基于功率最小化准则的鲁棒波束成形(Beamforming,BF)算法。考虑配置多根天线的UAV通过放大转发协议转发卫星信号的同时,采用认知无线电(Cognitive Radio,CR)技术与其自身用户进行通信,同时UAV接收到多个干扰信号的情况下,分别给出了各种用户的输出信干噪比(Signal-to-Interference-plus-Noise Ratio,SINR)表达式。在所有用户的信道状态信息存在误差的条件下,建立了以满足所有用户服务质量(Quality-of-Service,QoS)需求为约束,UAV发射功率最小化为目标函数的优化问题。考虑到该问题非凸,在数学上难以求解,于是提出了基于迫零(Zero-Forcing,ZF)和半正定规划相结合的求解方法,得到波束成形权矢量。计算机仿真验证了所提算法的鲁棒性和有效性。

A Beamforming(BF)algorithm based on power minimization criterion for a cognitive satellite and aerial cooperative network is proposed,where Unmanned Aerial Vehicle(UAV)acts as the relay station to assist satellite communication.Firstly,considering that multiple-antenna UAV forwards the satellite signal through amplify-and-forward protocol and adopts the Cognitive Radio(CR)technology to serve its own users,meanwhile suffered from multiple interference signal,the output Signal-to-Interference-plusNoise Ratio(SINR)expressions of various users are given respectively.Then,under the condition that there are errors in the channel states of all users,the optimization problem is formulated with the constraint of meeting the Quality-of-Service(QoS)requirements of all users and the objective function of minimizing the UAV transmission power.Since the problem is nonconvex and mathematically intractable,a method combining Zero-Forcing(ZF)and semidefinite programming is proposed to obtain the BF weight vectors.Finally,computer simulations verify the robustness and effectiveness of the proposed algorithm.