US 6,744,893 B1 · Receiver estimation engine for a chaotic system

Abstract

A chaotic receiver estimation engine and method of use. The estimation engine synchronizes and recovers data and performs its decision and tracking processes by mapping probability calculation results onto chaotic dynamics via a strange attractor geometrical approximation. Restrictive standard chaotic synchronization requirements of either a stable/unstable subspace separation or a chaotic system inversion are not required. The receiver determines and models both the logical zero and logical one versions of the strange attractor and the transmitted chaotic sequence probability density function (PDF). Two estimates of the transmitted value are created from each received iterate by probability and the transmitted PDF calculations. A third estimate is generated from the chaotic processing of the previous receiver final decisions. The three estimates are combined using a probability-based weighted average to form the initial current decision. A final current decision incorporates chaotic dynamics by mapping the initial decision onto the geometrical model of the attractors via a minimum Euclidean distance metric.

Claims67

Dependent claims

A nonlinear chaotic receiver comprising a component for receiving a chaotic encoded digital signal transmission from a chaotic transmitter, synchronizing the chaotic receiver with the chaotic transmitter and recovering the contents of the encoded chaotic digital signal transmission using a chaotic strange attractor model and a chaotic probability density function model, wherein:

a. synchronization of the chaotic receiver with the chaotic transmitter and recovery of the contents of the encoded chaotic digital signal transmission occurs in the same calculations and results concurrently from the same calculations,
b. the chaotic encoded digital signal transmission is a data sequence comprising a first through N number of iterates, wherein the first iterate represents a first value in the data sequence and the Nth iterate represents a last value in the data sequence;
and
c. the chaotic strange attractor model comprises:
i. a strange attractor generated by combining Henon and mirrored Henon attractors, wherein the Henon and mirrored Henon attractors are generated by starting with one or more arbitrary points within an area of phase space that stretches and folds back onto itself, and inputting the points to a set of Henon equations, the result being the Henon attractor, and taking a mirror image of the Henon attractor to form the mirrored Henon attractor;
ii. the strange attractor represented as a set of parabolas displayed on a Cartesian coordinate system;
and
iii. the parabolic regions of validity of the strange attractor determined.

5 more elements

a. synchronization of the chaotic receiver with the chaotic transmitter and recovery of the contents of the encoded chaotic digital signal transmission occurs in the same calculations and results concurrently from the same calculations;
b. the chaotic encoded digital signal transmission is a data sequence comprising a first through N number of iterates, wherein the first iterate represents a first value in the data sequence and the Nth iterate represents a last value in the data sequence:
the nonlinear chaotic receiver further comprising means for determining the contents of the encoded chaotic digital signal transmission including:
c. three estimates generated for each iterate received and an initial decision calculated for each iterate;
d. the initial decision mapped onto the chaotic attractor to form a final decision for each estimate;
and
e. a discount weight calculated to reduce the impact of the initial decisions whose receive values are close to zero.

4 more elements

A nonlinear chaotic receiver comprising:

a. a receiver estimation engine for synchronizing the chaotic receiver with a chaotic transmitter and recovering the value of an encoded chaotic digital signal transmission, the receiver estimation engine comprising:
i. a signal-to-noise ratio (SNR) estimator;
ii. a maximum a posteriori (MAP) estimator;
iii. a feedback estimator;
iv. wherein the chaotic receiver and the chaotic transmitter synchronization and the encoded digital signal transmission recovery occur concurrently while executing the same set of calculations within the receiver estimation engine;
b. a decision and weighting function within the receiver estimation engine comprising:
i. probability of transmit value estimates determined using the SNR estimator, the MAP estimator and the feedback estimator for each received iterate;
ii. an initial decision calculated for the iterate;
iii. a discount weight calculated for a final decision for received values in close proximity to zero;
c. within the receiver estimation engine, the final estimate of each iterate determined based on the initial decision from the decision and weighting function;
and
d. within the receiver estimation engine, the final decision of iterates 1 through N combined to recover the encoded digital signal transmission data sequence.

9 more elements

A method in a computer system of receiving and recovering the contents of a chaotic encoded digital signal transmission comprising:

a. receiving a chaotic encoded digital signal transmission from a chaotic transmitter;
b. synchronizing the chaotic receiver with the chaotic transmitter;
and
c. recovering the contents of the encoded chaotic digital signal transmission using a chaotic strange attractor model and a chaotic probability density function model,
d. wherein:
i. the synchronizing of the chaotic receiver with the chaotic transmitter and recovering of the contents of the encoded chaotic digital signal transmission occurs in the same calculations and results concurrently from the same calculations;
ii. the receiving a chaotic encoded digital signal transmission is a data sequence comprising a first through N number of iterates, wherein the first iterate represents a first value in the data sequence and the Nth iterate represents a last value in the data sequence;
iii. the using of a chaotic strange attractor model comprises:
1. generating a strange attractor by combining Henon and mirrored Henon attractors, wherein the Henon and mirrored Henon attractors are generated by starting with one or more arbitrary points within an area of phase space that stretches and folds back onto itself, and inputting the points to a set of Henon equations, the result being the Henon attractor, and taking a mirror image of the Henon attractor to form the mirrored Henon attractor;
2. representing the strange attractor as a set of parabolas displayed on a Cartesian coordinate system;
and
3. determining the parabolic regions of validity of the strange attractor.

9 more elements

A method in a computer system of receiving and recovering the contents of a chaotic encoded digital signal transmission comprising:

a. receiving a chaotic encoded digital signal transmission from a chaotic transmitter;
b. synchronizing the chaotic receiver with the chaotic transmitter;
and
c. recovering the contents of the encoded chaotic digital signal transmission using a chaotic strange attractor model and a chaotic probability density function model
d. wherein:
i. the synchronizing of the chaotic receiver with the chaotic transmitter and recovering of the contents of the encoded chaotic digital signal transmission occurs in the same calculations and results concurrently from the same calculations;
ii. the receiving a chaotic encoded digital signal transmission is a data sequence comprising a first through N number of iterates, wherein the first iterate represents a first value in the data sequence and the Nth iterate represents a last value in the data sequence;
and
e. determining the contents of the encoded chaotic digital signal transmission by:
i. generating three estimates for each iterate received and calculating an initial decision for each iterate;
ii. mapping the initial decision on onto the chaotic attractor to form a final decision for each estimate;
and
iii. calculating a discount weight to reduce the impact of the initial decisions whose receive values are close to zero.

10 more elements

A method in computer system of receiving and recovering the contents of a chaotic encoded digital signal transmission comprising:

a. synchronizing a chaotic receiver with a chaotic transmitter and recovering an encoded chaotic digital signal transmission using a receiver estimation engine,
said engine comprising:
i. a signal-to-noise ratio (SNR) estimator;
ii. a maximum a posteriori (MAP) estimator;
iii. a feedback estimator;
iv. wherein the chaotic receiver and the chaotic transmitter are synchronized and the encoded digital signal transmission are recovered concurrently when executing the same set of calculations within the receiver estimation engine;
b. using a decision and weighting function within the receiver estimation engine comprising:
i. determining the probability of transmit value estimates using the SNR estimator, the MAP estimator and the feedback estimator for each received iterate;
ii. calculating an initial decision for the iterate;
iii. calculating a discount weight for a final decision for received values in close proximity to zero;
c. determining the final value of each iterate based on the initial decision from the decision and weighting function;
and
d. combining the final decision of iterates 1 through N to recover the encoded digital signal transmission data sequence.

10 more elements

Dependencies are inferred from the claim text.

Receiver estimation engine for a chaotic system

Life of this patent

Receiver estimation engine for a chaotic system

Life of this patent

Abstract

Claims67