| 摘要: |
| 以低轨卫星通信系统能量效率最大化为优化目标，重点研究鲁棒波束成形设计。假设卫星侧配备大规模多输入多输出技术，综合考虑传播延迟和多普勒频移造成的信道状态信息误差影响，在发射功率受限和用户服务质量约束下，提出了一种鲁棒高效的波束成形方案。考虑到遍历用户速率和遍历信干噪比都没有闭合表达式，采用具备闭合表达式的近似值代替，同时，采用半正定规划算法将非凸二次约束二次规划形式问题进行等价转换，并提出了一种联合二次变换分式规划和凹凸过程的内外两层嵌套迭代算法。最后，采用一种惩罚函数算法解决半正定规划算法中存在的秩1约束问题。仿真结果表明，所提算法性能优于传统算法，且鲁棒性较高。 |
| 关键词: 低轨卫星通信系统 大规模多输入多输出 能量效率 鲁棒算法 波束成形 |
| DOI：10.20079/j.issn.1001-893x.220324007 |
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| 基金项目:北京市重大科技专项（Z181100002918004） |
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| Robust and efficient beamforming design for Massive MIMO LEO satellite communication system |
| LIU Yang,LI Changqing,LI Jiong,WU Min,FENG Lu |
| (Graduate School,Space Engineering University,Beijing 101400，China;School of Space Information,Space Engineering University,Beijing 101400，China) |
| Abstract: |
| This paper focuses on the design of robust beamforming to maximize the energy efficiency of low Earth orbit（LEO） satellite communication systems.Assuming that the LEO satellite antenna architecture adopts the massive multiple-input multiple-output(MIMO) technology,considering the influence of channel state information errors caused by propagation delay and Doppler shift,under the constraints of transmission power and quality of service,a robust energy-efficient beamforming scheme is proposed.Since that there are no explicit expressions for the ergodic user rate and the ergodic signal-to-interference-plus-noise ratio,the approximate values with closed-form expressions are adopted.Then,the semidefinite programming algorithm is used to convert the nonconvex quadratic constrained quadratic programming problem equivalently,and an inner and outer nested iterative algorithm combining quadratic transformation fractional programming and concave-convex procedure is proposed.Finally,a penalty function algorithm is used to handle the rank 1 constraint problem in semidefinite programming algorithm.Simulation results show that the performance of the proposed algorithm is better than that of traditional algorithms,and the robustness is higher. |
| Key words: LEO satellite communication system massive multiple input multiple output energy efficiency robust algorithm beamforming |
