Partition-Based Hybrid Decoding (PHD): A Class of ML Decoding Schemes for MIMO Signals Based on Tree Partitioning and Combined Depth- and Breadth-First Search
Fuente:
Redalyc
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Artículo científico |
| Sprache: | en |
| Veröffentlicht: |
Universidad Nacional Autónoma de México
2013
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1876463917196115968 |
|---|---|
| author | J. I. Park |
| author_facet | J. I. Park |
| contents | Partition-Based Hybrid Decoding (PHD): A Class of ML Decoding Schemes for MIMO Signals Based on Tree Partitioning and Combined Depth- and Breadth-First Search J. I. Park Y. Lee S. Yoon Ingeniería Hybrid decoding tree partitioning maximum likelihood detection multiple input multiple output (MIMO) In this paper, we propose a hybrid maximum likelihood (ML) decoding scheme for multiple-input multiple-output (MIMO) systems. After partitioning the searching tree into several stages, the proposed scheme adopts the combination of depth- and breadth-first search methods in an organized way. Taking the number of stages, the size of signal constellation, and the number of antennas as the parameter of the scheme, we provide extensive simulation results for various MIMO communication conditions. Numerical results indicate that, when the depth- and breadth-first search methods are employed appropriately, the proposed scheme exhibits substantially lower computational complexity than conventional ML decoders while maintaining the ML bit error performance. 2013 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47426225005 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.2 Vol.11 |
| format | Artículo científico |
| id | redalyc_47426225005 |
| institution | Redalyc |
| language | en |
| publishDate | 2013 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Partition-Based Hybrid Decoding (PHD): A Class of ML Decoding Schemes for MIMO Signals Based on Tree Partitioning and Combined Depth- and Breadth-First Search J. I. Park Ingeniería Hybrid decoding tree partitioning maximum likelihood detection multiple input multiple output (MIMO) Partition-Based Hybrid Decoding (PHD): A Class of ML Decoding Schemes for MIMO Signals Based on Tree Partitioning and Combined Depth- and Breadth-First Search J. I. Park Y. Lee S. Yoon Ingeniería Hybrid decoding tree partitioning maximum likelihood detection multiple input multiple output (MIMO) In this paper, we propose a hybrid maximum likelihood (ML) decoding scheme for multiple-input multiple-output (MIMO) systems. After partitioning the searching tree into several stages, the proposed scheme adopts the combination of depth- and breadth-first search methods in an organized way. Taking the number of stages, the size of signal constellation, and the number of antennas as the parameter of the scheme, we provide extensive simulation results for various MIMO communication conditions. Numerical results indicate that, when the depth- and breadth-first search methods are employed appropriately, the proposed scheme exhibits substantially lower computational complexity than conventional ML decoders while maintaining the ML bit error performance. 2013 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47426225005 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.2 Vol.11 |
| title | Partition-Based Hybrid Decoding (PHD): A Class of ML Decoding Schemes for MIMO Signals Based on Tree Partitioning and Combined Depth- and Breadth-First Search |
| topic | Ingeniería Hybrid decoding tree partitioning maximum likelihood detection multiple input multiple output (MIMO) |
| url | https://www.redalyc.org/articulo.oa?id=47426225005 |