LOW-COMPLEXITY LLR COMPUTATION FOR NONUNIFORM QAM CONSTELLATIONS

Patent №

US 10,003,436

Granted

2018-06-19

Filed 2017

Owner

KABUSHIKI KAISHA TOSHIBA

Lab

AI components

2

kr · planning

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

15472959

A device for use in demodulating modulated signals by determining a value for a log likelihood ratio. The device has a storage device to store executable instructions and a processor to execute the instructions stored on the memory device. The processor is configured to, when executing the instructions: receive a modulated signal which is to be demodulated using a constellation diagram comprising a plurality of constellation points which are identified by binary reflected Gray-labelled codes; identify, for a bit of the Gray-labelled codes, a closest complementary constellation point to the signal when considering the signal as a point on a representation of one-dimension of the constellation diagram; identify a hard decision point, wherein the hard decision point is the closest constellation point to the signal when considering the signal as a point on a representation of one-dimension of a constellation diagram; and a complementary constellation point is a constellation point which has a different value for the bit compared to the hard decision point; and determine a value for a log likelihood ratio using the hard decision point and the closest complementary constellation point. Some devices identify a closest complementary constellation point to the signal, a second closest complementary constellation point to the signal, a hard decision point and an auxiliary hard decision point and determine a value for a log likelihood ratio using the hard decision point, an auxiliary hard decision point, the closest complementary constellation point and the second closest complementary constellation point.

Knowledge representationPlanningH04L 1/0054H04L 27/38H04L 1/0016

AI classification

Knowledge representation1.00
Planning0.99
Evolutionary computation0.11
Vision0.03
Natural language0.02
AI hardware0.01
Speech0.00
Machine learning0.00

Ownership

KABUSHIKI KAISHA TOSHIBA

assignment · 426600355

Assignors

TOSATO, FILIPPO, ISMAIL, AMR, SANDELL, MAGNUS STIG TORSTEN

On an employer assignment, the assignors are typically the inventors.

From the same owner

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