Efficient near-ML decoding via statistical pruning

被引：0

作者：

Gowaikar, R ^{[1
]}

Hassibi, B ^{[1
]}

机构：

[1] CALTECH, Dept Elect Engn, Pasadena, CA 91125 USA

来源：

2003 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY - PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Maximum-likelihood (ML) decoding often reduces to finding the closest (skewed) lattice point in N-dimensions to a given point x is an element of C-N. Sphere decoding is an algorithm that does this. We modify the sphere decoder to reduce the computational complexity of decoding while maintaining near-ML performance.

引用

页码：274 / 274

页数：1

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