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首页> 外文会议>Information Sciences and Systems, 2009. CISS 2009 >Near-capacity performance soft output sphere decoding based on short list detection and metrics combining
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Near-capacity performance soft output sphere decoding based on short list detection and metrics combining

机译：基于短列表检测和度量组合的近容量性能软输出球解码

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摘要

We introduce a low complexity iterative soft output sphere decoding algorithm for coded transmissions over multiple antenna channels. Before the iterative detection and decoding starts, a modified hard decision sphere decoder produces a short (base) list of vectors with maximum likelihood metrics. In subsequent iterative soft detections, two competing lists with a small number of vectors are further generated for each coded bit, by utilizing the base list vectors and a priori information from the channel decoder. The corresponding likelihood metrics of the vectors in each competing list are combined to produce soft detection output that approximates the optimal maximum a posteriori (MAP) solution. The performance improves as the base list size increases and a short list (hence a low number of competing vectors) can provide near-capacity performance after a few iterations. Compared with existing methods that adopt the max-log approximation and select only a single best competing vector, the proposed algorithm approaches the optimal performance better with significantly lower complexity requirements.
机译：我们介绍了一种低复杂度的迭代软输出球解码算法，用于在多个天线信道上的编码传输。在迭代检测和解码开始之前，经过修改的硬决策球解码器会生成具有最大似然度量的简短矢量列表（基本列表）。在随后的迭代软检测中，通过利用基本列表矢量和来自信道解码器的先验信息，进一步为每个编码位生成两个带有少量矢量的竞争列表。将每个竞争列表中向量的相应似然度度量组合在一起，以产生软检测输出，该输出近似最佳最优后验（MAP）解决方案。随着基本列表大小的增加，性能会提高，而短列表（因此，竞争矢量的数量较少）可以在几次迭代后提供接近容量的性能。与采用最大对数近似并仅选择单个最佳竞争向量的现有方法相比，该算法以较低的复杂度要求更好地实现了最佳性能。

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