An ML Decoding Algorithm with Reduced Complexity for Multi-Input Multi-Output Systems

In this paper, employing the 'breadth-first' search algorithm for the decoding of received signals in multi-input multi-output systems, we propose a novel decoder exhibiting the maximum likelihood performance with reduced complexity. The proposed algorithm is compared with the sphere decod...

Full description

Saved in:
Bibliographic Details
Main Authors: Hyun Gu Kang, Juho Park, Taehun An, Jongho Oh, Iickho Song
Format: Conference Proceeding
Language:English
Subjects:
Bit error rate
breadth-first searching
Computational complexity
Euclidean distance
Lattices
Maximum likelihood decoding
Maximum likelihood detection
MIMO
multi-input multi-output system
Receiving antennas
sphere decoder
Transmitters
Transmitting antennas
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, employing the 'breadth-first' search algorithm for the decoding of received signals in multi-input multi-output systems, we propose a novel decoder exhibiting the maximum likelihood performance with reduced complexity. The proposed algorithm is compared with the sphere decoder. Simulation results show that the proposed decoder allows significantly lower computational complexity than the sphere decoder.
ISSN:2161-0819
DOI:10.1109/ISSSE.2007.4294482