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Low Complexity ML-Detection of Arbitrary Spherical Codes

机译:任意球码的低复杂度ML检测

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We present two algorithms that quantize arbitrary points to a given constellation efficiently, even though there may not be an analytic description of this constellation. We choose spherical codes as constellations, because the best spherical codes can often only be computed numerically. The quantization is equivalent to a maximum likelihood-detection, but the average number of operations can be greatly reduced. The comparison between our proposed algorithms and a brute force approach is done by numerical simulations.
机译:我们提出了两种算法,其有效地量化任意点到给定的星座,即使可能没有对该星座的分析描述。我们选择球形代码作为星座,因为最好的球形代码通常只能在数字上计算。量化相当于最大似然性检测,但是可以大大减少平均操作次数。我们所提出的算法与蛮力方法之间的比较是通过数值模拟完成的。

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