US 12,261,723 B2
Detector for faster than nyquist transmitted data symbols
Ahmed Mohamed Ali Ibrahim, Ottawa (CA); Ebrahim Bedeer, Saskatoon (CA); and Halim Yanikomeroglu, Ottawa (CA)
Assigned to CARLETON UNIVERSITY, Ontario (CA); and UNIVERSITY OF SASKATCHEWAN, SASKATOON, Saskatchewan (CA)
Appl. No. 18/277,449
Filed by CARLETON UNIVERSITY, Ottawa (CA)
PCT Filed Feb. 16, 2022, PCT No. PCT/IB2022/051391
§ 371(c)(1), (2) Date Aug. 16, 2023,
PCT Pub. No. WO2022/175846, PCT Pub. Date Aug. 25, 2022.
Claims priority of provisional application 63/150,798, filed on Feb. 18, 2021.
Prior Publication US 2024/0305506 A1, Sep. 12, 2024
Int. Cl. H04L 25/03 (2006.01)
CPC H04L 25/03178 (2013.01) 20 Claims
OG exemplary drawing
 
1. A data processor block for use in a data receiver system, the data processor block comprising:
a data processor for processing a received signal, said received signal being received by said data receiver system, said data processor being for estimating a sequence of data symbols in said received signal, said symbols having been transmitted at a rate faster than a Nyquist rate;
wherein said data processor implements a method comprising:
a) receiving an input matrix, a received samples vector, received samples in said received samples vector being from said received signal;
b) preconditioning said input matrix and said received samples vector to result in a prepared input matrix and a prepared received samples vector;
c) performing a factorization of prepared input matrix;
d) initializing a best estimate vector;
e) initializing a current estimate vector, a current multipliers vector, and a current auxiliary vector;
f) executing steps (f1)-(f4);
g) repeating step f) for a predetermined number of iterations;
h) repeating steps (e)-(g) for a predetermined number of initializations;
i) outputting said best estimate vector as said estimate for said sequence of data symbols;
wherein steps (f1)-(f4) comprises:
f1) calculating a next estimate vector for said sequence of data symbols based on said prepared input matrix, said prepared received samples vector, a current estimate vector, a current multipliers vector, and a current auxiliary vector,
f2) calculating a next auxiliary vector based on said next estimate vector and said current multipliers vector;
f3) calculating a next multipliers vector based on said current multipliers vector, said next estimate vector, and said next auxiliary vector;
f4) assessing a calculated current function value using said current estimate vector and comparing said calculated current function value with a result of assessing a best estimate function value and, if said calculated current function value is less than said result of assessing said best estimate function value, storing said current estimate vector as said best estimate vector.