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An ML Decoding Algorithm with Reduced Complexity for Multi-Input Multi-Output Systems
By: Iickho Song; Jongho Oh; Taehun An; Juho Park; Hyun Gu Kang;
2007 / IEEE / 1-4244-1448-2
Description
This item was taken from the IEEE Conference ' 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 decoder. Simulation results show that the proposed decoder allows significantly lower computational complexity than the sphere decoder.
Related Topics
Computational Complexity
Ml Decoding Algorithm
Reduced Complexity
Multi-input Multi-output Systems
Breadth-first Search Algorithm
Maximum Likelihood Decoding
Sphere Decoder
Maximum Likelihood Decoding
Mimo
Receiving Antennas
Bit Error Rate
Transmitting Antennas
Computational Complexity
Transmitters
Maximum Likelihood Detection
Euclidean Distance
Lattices
Sphere Decoder
Maximum Likelihood Detection
Multi-input Multi-output System
Breadth-first Searching
Mimo Communication
Maximum Likelihood Decoding
Computational Complexity
Codecs
Tree Searching
Engineering
Signal Decoding