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Interference management via cooperative beam biasing and power control for mmWave satellite clusters
International Journal of Satellite Communications and Networking ( IF 1.7 ) Pub Date : 2021-04-07 , DOI: 10.1002/sat.1400
Shanghong Zhang 1 , Gaofeng Cui 1, 2, 3 , Pengxu Li 4 , Weidong Wang 1, 2
Affiliation  

In order to tackle the problem of spectrum scarcity, spectrum sharing among satellite communication systems becomes a common phenomenon. Due to the spectrum sharing, mmWave satellite cluster, which is considered as a prominent part of the space information networks, may suffer severe mutual interference among inter-satellite data links. In this paper, we firstly conduct the interference analysis for satellite clusters. Then, we formulate the interference problem as a constrained optimization problem in the performance metric of the total achievable data rate. To alleviate the interference between satellite clusters, a particle swarm optimization (PSO)-based cooperative beam biasing and power control scheme (CBP-PSO) from the perspectives of the joint beam domain and power domain is proposed. And the interference management problem is transformed to find the best combination of the boresight direction and transmission power based on the improved PSO algorithm. Specially, in the interference analysis and proposed scheme, different satellite cluster formations and antenna configurations are taken into account. Finally, simulation results show that the proposed CBP-PSO scheme based on cooperative beam biasing and power control can effectively improve the achievable data rate of the interfered data links, even for the severe in-line interference.

中文翻译:

通过协作波束偏置和功率控制对毫米波卫星集群进行干扰管理

为了解决频谱稀缺问题,卫星通信系统之间的频谱共享成为普遍现象。由于频谱共享,作为空间信息网络重要组成部分的毫米波卫星集群可能会受到星间数据链路之间严重的相互干扰。在本文中,我们首先对卫星群进行干扰分析。然后,我们将干扰问题表述为总可实现数据速率的性能指标中的约束优化问题。为了减轻星群之间的干扰,从联合波束域和功率域的角度提出了一种基于粒子群优化(PSO)的协作波束偏置和功率控制方案(CBP-PSO)。并基于改进的PSO算法将干扰管理问题转化为寻找视轴方向和发射功率的最佳组合。特别地,在干扰分析和提出的方案中,考虑了不同的卫星簇编队和天线配置。最后,仿真结果表明,所提出的基于协作波束偏置和功率控制的 CBP-PSO 方案可以有效提高受干扰数据链路的可实现数据速率,即使对于严重的在线干扰也是如此。
更新日期:2021-04-07
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