IP Library Granted Patent US 9,215,102
Granted Patent B2
US 9,215,102 · App. 14/326,708 · Granted Dec 15, 2015

Hypotheses generation based on multidimensional slicing

Inventors: Amir Eliaz (Moshav Ben Shemen, IL); Ilan Reuven (Ganey Tikva, IL); Gal Pitarasho (Tel Aviv, IL)
Assignee: MagnaCom Ltd.
H04L25/03006H04L25/03222H04L27/38
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Quick Facts
Patent No.
US 9,215,102
App. No.
14/326,708
Granted
Dec 15, 2015
Kind
B2
Abstract

A receiver is configured to receive a sample of an inter-symbol correlated (ISC) signal, the sample corresponding to a time instant when phase and/or amplitude of the ISC signal is a result of correlation among a plurality of symbols of a transmitted symbol sequence. The receiver may linearize the sample of the ISC signal. The receiver may calculate a residual signal value based on the linearized sample of the ISC signal. The receiver may generate an estimate of one or more of said plurality of symbols based on a slicing of the residual signal value. The linearization may comprise applying an estimate of an inverse of a non-linear model. The non-linear model may be a model of nonlinearity experienced by the ISC signal in a transmitter from which the ISC signal originated, in a channel through which the ISC signal passed en route to the receiver, and/or in a front-end of the receiver.

Claims (25)

1. A system comprising:

a receiver configured to:

receive a sample of an inter-symbol correlated (ISC) signal, said sample corresponding to a time instant when phase and/or amplitude of said ISC signal is a result of correlation among a plurality of symbols of a transmitted symbol sequence;

linearize said sample of said ISC signal;

calculate a residual signal value based on said linearized sample of said ISC signal; and

generate an estimate of one or more of said plurality of symbols based on a slicing of said residual signal value, wherein said slicing is performed via a look-up table.

2. The system of claim 1 , wherein:

said linearization comprises applying an estimate of an inverse of a non-linear model.

3. The system of claim 2 , wherein said non-linear model is a model of nonlinearity experienced by said ISC signal in a transmitter from which said ISC signal originated.

4. The system of claim 2 , wherein said non-linear model is a model of nonlinearity experienced by said ISC signal in a channel through which said ISC signal passed en route to said receiver.

5. The system of claim 2 , wherein said non-linear model is a model of nonlinearity experienced by said ISC signal in a front-end of said receiver.

6. The system of claim 1 , wherein said receiver is configured to, subsequent to said linearization and prior to said generation of said estimate of said one or more of said plurality of symbols, filter said sample of said ISC signal.

7. The system of claim 1 , wherein:

said receiver is configured to generate one or more branch vector hypotheses based on said residual signal value;

each of said one or more branch vector hypotheses comprises a plurality of symbols; and

said receiver is configured to generate said estimate of said one or more of said plurality of symbols based one or more branch vector hypotheses.

8. The system of claim 7 , wherein:

a quantity of branch vector hypotheses in said one or more branch vector hypotheses is larger for a sample of said ISC signal corresponding to a residual signal value that is relatively close to a center of a multidimensional partial lattice; and

said quantity of branch vector hypotheses in said one or more branch vector hypotheses is smaller for a sample of said ISC signal corresponding to a residual signal value that is relatively far from said center of said multidimensional partial lattice.

9. The system of claim 7 , wherein a quantity of branch vector hypotheses is determined based on a signal-to-noise ratio.

10. The system of claim 7 , wherein a quantity of said one or more branch vector hypotheses is determined based on an amount of non-linear distortion experienced by said ISC signal.

11. The system of claim 7 , wherein said receiver is configured to generate said one or more branch vector hypotheses based on a minimal Euclidean distance criterion.

12. The system of claim 7 , wherein said receiver is configured to generate said one or more branch vector hypotheses based on a diversity-distance criterion.

13. The system of claim 1 , wherein said estimate of said one or more of said plurality of symbols is a soft-decision.

14. The system of claim 13 , wherein said soft decision is weighted based on said residual signal value.

Assignments (3)
CORRECTIVE ASSIGNMENT TO CORRECT THE EXECUTION DATE PREVIOUSLY RECORDED AT REEL: 047422 FRAME: 0464. ASSIGNOR(S) HEREBY CONFIRMS THE MERGER. Recorded Mar 6, 2019
From: AVAGO TECHNOLOGIES GENERAL IP (SINGAPORE) PTE. LTD.
To: AVAGO TECHNOLOGIES INTERNATIONAL SALES PTE. LIMITED
Reel/Frame 048883/0702 →
MERGER Recorded Oct 5, 2018
From: AVAGO TECHNOLOGIES GENERAL IP (SINGAPORE) PTE. LTD.
To: AVAGO TECHNOLOGIES INTERNATIONAL SALES PTE. LIMITED
Reel/Frame 047422/0464 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 2, 2017
From: MAGNACOM LTD.
To: AVAGO TECHNOLOGIES GENERAL IP (SINGAPORE) PTE. LTD.
Reel/Frame 041604/0861 →
Continuity (2)
Continuation 14079465 · Nov 13, 2013
Related Publication 20150131759A1 · May 14, 2015