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
Document 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
Journal: Journal of applied research and technology
Database: PERIÓDICA
System number: 000377607
ISSN: 1665-6423
Authors: 1
1
1
Institutions: 1Sungkyunwan University, College of Information and Communication Engineering, Suwon. Corea del Sur
Year:
Season: Abr
Volumen: 11
Number: 2
Pages: 213-224
Country: México
Language: Inglés
Document type: Artículo
Approach: Experimental, aplicado
English abstract 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
Disciplines: Ingeniería
Keyword: Ingeniería de telecomunicaciones,
Decodificación híbrida,
Sistemas MIMO,
Particionamiento de señales
Keyword: Engineering,
Telecommunications engineering,
Hybrid decoding,
MIMO systems,
Signal partitioning
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