Closed-Form Power Normalization Methods for a Satellite MIMO System.
Closed-Form Power Normalization Methods for a Satellite MIMO System.
复制标题
卫星MIMO系统的闭式功率归一化方法。
DOI：
10.3390/s22072586
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发表时间：
2022-03-28
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影响因子：
--
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文献类型：
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提出了一种适用于宽带多用户多输入多输出(MIMO)卫星系统的预编码/波束形成矩阵归一化新技术。所提出的技术采用已知的归一化方法来考虑由于天线增益的退化和覆盖边缘的自由空间损耗而导致的用户所经历的信号衰减。我们以地球同步轨道(GEO)卫星上的阵列馈电反射器(AFR)天线为例，它在高方向性、可重构性和数字处理要求之间提供了有利的折衷，但在全球覆盖应用中，由于光学象差而导致远离宽边的高扫描损耗。采用了三种不同的预编码/波束形成技术，即迫零(ZF)、最小均方误差(MMSE)和匹配滤波(MF)。引入了在波束形成器之后数字应用的低复杂性功率归一化技术，在没有任何大气影响的情况下，在满足每个馈电的功率限制的同时，导致了等磁通特性。与文献中报道的主要基于迭代算法的其他方法相比，所提出的技术存在于闭合形式的表达式中，以在不显著影响净荷和速率的情况下提供跨用户的均匀信噪比(SNR)和信噪比加干扰比(SNIR)。数值结果表明，在不同的噪声和干扰情况下，系统在总容量和信噪比分布方面都能达到较好的性能。
The paper proposes a new set of normalization techniques for precoding/beamforming matrices applicable to broadband multiuser multiple-input multiple-output (MIMO) satellite systems. The proposed techniques adapt known normalization methods to account for the signal attenuation experienced by users due to the degradation of antenna gain and free space losses towards the edge of the coverage. We use, as an example, an array-fed reflector (AFR) antenna onboard a satellite in geosynchronous orbit (GEO), which provides a favorable trade-off between high-directivity, reconfigurability, and the requirement for digital processing, but suffers from high scan losses away from broadside due to optical aberrations when considered for global coverage applications. Three different precoding/beamforming techniques are employed, namely zero forcing (ZF), minimum mean squared error (MMSE), and matched filtering (MF). Low-complexity power normalization techniques digitally applied after the beamformer are introduced that, in the absence of any atmospheric effects, lead to iso-flux-like characteristics whilst satisfying the power constraint per feed. In comparison with other methods reported in the literature, mainly based on iterative algorithms, the proposed techniques consist in closed-form expressions to provide uniform signal-to-noise ratio (SNR) and signal-to-noise plus interference ratio (SNIR) across the users without significant impact on the payload sum rate. Numerical results are presented to comparatively demonstrate the achieved performance in terms of total capacity and distribution of SNR and SNIR at various noise and interference scenarios.
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DOI：
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发表时间：
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影响因子：
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