Published 2003
| Version Published
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Efficient near-ML decoding via statistical pruning
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Abstract
Maximum-likelihood (ML) decoding often reduces to finding the closest (skewed) lattice point in N-dimensions to a given point x ϵ 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.
Additional Information
© 2003 IEEE. This work was supported in part by the National Science Foundation under grant no. CCR-0133818, by the office of Naval Research under grant no. N00014-02-1-0578, and by Caltech's Lee Center for Advanced Networking.Attached Files
Published - 01228289.pdf
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01228289.pdf
Additional details
Identifiers
- Eprint ID
- 55295
- Resolver ID
- CaltechAUTHORS:20150227-071358104
Funding
- NSF
- CCR-0133818
- Office of Naval Research (ONR)
- N00014-02-1-0578
- Caltech's Lee Center for Advanced Networking
Dates
- Created
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2015-02-27Created from EPrint's datestamp field
- Updated
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2021-11-10Created from EPrint's last_modified field