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Revisit on maximum ratio combining reception practically attained across correlated Nakagami-m branches

机译:重新审视最大比率,相结合的接收实际上跨越相关的Nakagami-M分支

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First- and second-order statistics that can be attained at a practical receiver via maximum-ratio combining (MRC) reception across correlated Nakagami-m branches are studied in this paper. A lump sum of the branch weight squares is employed in the conventional analysis of the MRC reception. The conventional MRC reception whose first- and second-order statistics were only derived on a noise-free condition can never be achieved in practice because the branches, which are smeared by crosscorrelation and are corrupted by noise, can only be statistically specified and they must be considered of as stochastic processes at the receiver, instead of deterministic time functions. The proposed method, in fact, considers the branch weights as stochastic processes and effectively restores diversity by the assistance from a linear transformation. Significant component selection combining (SCSC) can hence be applied not only to simplify the inner receiver but also to reduce the estimation error and the thermal noise. The MRC reception is then conducted with assistance from estimates of the decorrelated branches that are selected by the SCSC methods. The performance merit figures, i.e., first- and second-order statistics, must be redefined in the post-inner-receiving sense to provide sufficient and accurate information required for the design or the derivations of the outer receiving techniques or algorithms. The first- and second-order statistics of the MRC reception over the significant decorrelated diversity branches were verified by computer simulations.
机译:本文研究了通过最大比率(MRC)接收在实用接收器处获得的第一和二阶统计数据。在MRC接收的常规分析中采用分支体重方块的一块块。传统的MRC接收,其第一阶和二阶统计仅导出无噪声条件,因此不能在实践中实现,因为通过跨围机涂抹并被噪声损坏的分支,只能在统计上指定并且必须被认为是接收器处的随机过程,而不是确定性时间函数。实际上,该方法认为分支权重作为随机过程,并通过线性变换的辅助有效地恢复多样性。因此,不仅可以应用显着的组件选择组合(SCSC),以简化内部接收器,而且还可以减少估计误差和热噪声。然后通过SCSC方法选择的去相关分支的估计来进行MRC接收。在后内接收意义上必须重新定义性能优异图,即第一和二阶统计信息,以提供设计或外部接收技术或算法的推导所需的足够和准确的信息。通过计算机模拟验证了通过显着的去相关分集分支的MRC接收的第一和二阶统计。

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