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A Complexity Efficient DMT-Optimal Tree Pruning Based Sphere Decoding

机译:一种复杂性高效的DMT - 最优树修剪基于球体解码

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We present a diversity multiplexing tradeoff (DMT) optimal tree pruning sphere decoding algorithm which visits merely a single branch of the search tree of the sphere decoding (SD) algorithm, while maintaining the DMT optimality at high signal to noise ratio (SNR) regime. The search tree of the sphere decoding algorithm is pruned via intersecting one dimensional spheres with the hypersphere of the SD algorithm, and the radii are chosen to guarantee the DMT optimality. In contrast to the conventional DMT optimal SD algorithm, which is known to have a polynomial complexity at high SNR regime, we show that the proposed method achieves the DMT optimality by solely visiting a single branch of the search tree at high SNR regime. The simulation results are corroborated with the claimed characteristics of the algorithm in two different scenarios.
机译:我们介绍了一个多样化的多路复用权衡(DMT)最优树修剪球形解码算法,其仅访问球体解码(SD)算法的搜索树的单个分支,同时以高信号保持DMT最优性(SNR)制度。 球体解码算法的搜索树通过与SD算法的极度相交,并选择半径以保证DMT最优性。 与传统的DMT最佳SD算法相反,已知在高SNR制度下具有多项式复杂性,我们表明所提出的方法通过仅在高SNR制度下仅访问搜索树的单个分支来实现DMT最优性。 模拟结果与两种不同场景中的算法的要求保护特征进行了证实。

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