认知星⁃地融合无线网络中的波束形成算法研究

Investigation on beamforming algorithms for cognitive satellite⁃terrestrial integrated wireless networks

研究了认知星⁃地融合无线网络中的波束形成算法,存在地面窃听用户的卫星无线网络为主网络,地面蜂窝网络为次级网络,二者一起构成频谱共享的认知星⁃地融合无线网络。在认知星⁃地融合无线网络中,假设所有节点的信道状态信息完全已知。首先,以系统发射功率最小化为目标函数,卫星主用户的可达安全速率和次级用户的通信速率满足要求为约束条件建立优化问题。其次,利用迫零波束形成算法、门限值替代算法和黄金分割算法分别将原始非凸的优化问题转化为满足凸形式的优化问题,并通过半正定规划方法求解出优化问题的最优解。最后,计算机仿真结果验证了黄金分割算法具有更高的有效性及优越性。

This paper investigates three beamforming algorithms for cognitive satellite(SAT)⁃terrestrial integrated wireless networks.We regard the SAT wireless network with a capable eavesdropper as the primary network and terrestrial cellular network as the secondary network,and the primary SAT network shares the spectrum with the terrestrial network.Further,we assume that the channel state information(CSI)is completely known for this hybrid SAT⁃terrestrial wireless network.First,we build the optimization problem whose objective function is to minimize the total transmit power of the SAT and the terrestrial base station(BS)with the constraint that both the capable secrecy rate of the primary user and the communication rate of the secondary user are satisfied.Then,three algorithms,the zero⁃forcing,the threshold substitution and the golden search beamforming(BF),are used to convert the original non⁃convex optimization problem into the convex one,and the semi⁃definite program(SDP)technique is used to calculate the optimal BF vectors.Finally,simulation results verify the availability and superiority of the golden search BF algorithm.