Collaborative Beamforming for Cognitive UAV Relaying System Coexisting with Satellite Networks

Shengxiang Zhu, Ke Yang, J. Ouyang, Xiaohuan Wu, Luyao Xie
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Abstract

In this paper, we study a cognitive unmanned aerial vehicle (UAV) relaying system (CURS) which shares the downlink frequency of a satellite network. Specifically, we propose a collaborative beamforming (CBF) scheme that maximizes the signal-to-interference plus noise ratio (SINR) of CURS, subjects to the SINR requirements of the satellite network and the individual transmit power constraints of UAV relays. Since the original optimization problem is non-convex and mathematically intractable, we first transform it into an approximate convex one by means of the Charnes-Cooper transformation and the penalty function method as well as the difference of two-convex functions (D.C.) approach. Then a convergence proven iterative algorithm is designed to find the optimal CBF solution. Simulation results are provided to demonstrate the effectiveness of the proposed scheme and the impact of UAV transmit power and satellite network SINR requirements on the CURS.
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认知无人机中继系统与卫星网络共存的协同波束形成
研究了一种共享卫星网络下行频率的认知无人机中继系统(CURS)。具体而言,我们提出了一种协作波束形成(CBF)方案,该方案在满足卫星网络的信噪比要求和无人机中继的单个发射功率约束的情况下,最大限度地提高了CURS的信噪比。由于原优化问题是非凸的,在数学上难以处理,我们首先利用Charnes-Cooper变换和罚函数法以及双凸函数差分法(dc)将其转化为近似凸问题。然后设计了一种收敛性证明的迭代算法来寻找最优CBF解。仿真结果验证了所提方案的有效性,以及无人机发射功率和卫星网络信噪比要求对CURS的影响。
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