Reducing computational complexity in maximum likelihood MIMO...

Details Reducing computational complexity in maximum likelihood MIMO... Reducing computational complexity in maximum likelihood MIMO...

2011-03-22

2011-03-22

Fan, Chieh M (Department: 2611)

Pulse or digital communications

Systems using alternating or pulsating current

Plural channels for transmission of a single pulse train

C375S267000, C375S316000, C375S347000, C375S349000, C375S340000, C714S794000, C714S795000

Reexamination Certificate

active

07912140

ABSTRACT:
A method and a system for reducing computational complexity in a maximum-likelihood MIMO decoder, while maintaining its high performance. A factorization operation is applied on the channel Matrix H. The decomposition creates two matrixes: an upper triangular with only real-numbers on the diagonal and a unitary matrix. The decomposition simplifies the representation of the distance calculation needed for constellation points search. An exhaustive search for all the points in the constellation for two spatial streams t(1), t(2) is performed, searching all possible transmit points of (t2), wherein each point generates a SISO slicing problem in terms of transmit points of (t1); Then, decomposing x,y components of t(1), thus turning a two-dimensional problem into two one-dimensional problems. Finally searching the remaining points of t(1) and using Gray coding in the constellation points arrangement and the symmetry deriving from it to further reduce the number of constellation points that have to be searched.

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Ghosh et al, “Reduced complexity ML Detection for Coded MIMO System Using Absolute-Value Search,” published in Intl Conf on Acoustics, Speech and Signal Processing, 2005, vol. 3, pp. 1025-1028.

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