Granted Patent B2

US 12,417,374 · App. 18/577,217 · Granted Sep 16, 2025

Inventors: Sewoong Oh (Seattle, WA); Xiyang Liu (Seattle, WA); Hessam Mahdavifar (Ann Arbor, MI); Mohammad Vahid Jamali (Ann Arbor, MI); Pramod Viswanath (Champaign, IL); Ashok Makkuva (Champaign, IL)

Assignees: University of Washington; The Regents of the University of Michigan; The Board of Trustees of the University of Illinois

G06N3/0455G06N7/046H03M13/21H03M13/611

Abstract

Claims (39)

1. A method of encoding a set of information bits to produce a codeword that encodes the set of information bits for reliable communication, the method comprising:

receiving the set of information bits;

providing the set of information bits to a plurality of permutation layers separated by neural network processing layers, wherein each permutation layer accepts an input vector and generates a reordered output vector that is a reordering of the input vector, and wherein each neural network processing layer accepts a vector of input values and generates a vector of output values based on a non-linear function of the vector of input values; and

providing the reordered output vector of a final permutation layer of the plurality of permutation layers as the codeword.

2. The method of claim 1 , wherein each neural network processing layer includes a single neural network that accepts an entirety of the vector of input values.

3. The method of claim 1 , wherein each neural network processing layer includes a plurality of neural networks that each accepts a subset of the vector of input values.

4. The method of claim 3 , wherein for a given neural network processing layer, weights of each neural network in the plurality of neural networks are the same.

5. The method of claim 3 , wherein each neural network of the plurality of neural networks accepts a pair of input values from the vector of input values as input.

6. The method of claim 1 , wherein at least one neural network processing layer of the neural network processing layers uses SeLU activation.

7. The method of claim 1 , further comprising adding one or more zero values to pad the set of information bits to a size expected by the plurality of permutation layers and the plurality of neural network layers.

8. The method of claim 1 , wherein the codeword is a real-valued vector.

9. A method of reliable wireless transmission of a set of information bits, the method comprising:

determining a set of information bits to be transmitted;

encoding the set of information bits in a codeword; and

wirelessly transmitting the codeword;

wherein encoding the set of information bits in a codeword comprises a method as recited in claim 1 .

10. A method of decoding a codeword to retrieve a set of information bits, the method comprising:

receiving the codeword;

providing the codeword to a plurality of permutation layers separated by neural network processing layers, wherein each permutation layer accepts an input vector and generates a reordered output vector that is a reordering of the input vector, and wherein each neural network processing layer accepts a vector of input values and generates a vector of output values based on a non-linear function of the vector of input values; and

performing a plurality of forward calculations and backward calculations using the plurality of permutation layers separated by the neural network processing layers to retrieve the set of information bits.

11. The method of claim 10 , wherein performing the plurality of forward calculations and backward calculations using the plurality of permutation layers separated by the neural network processing layers to retrieve the set of information bits includes:

performing a forward calculation;

extracting an information bit of the set of information bits from a result of the forward calculation;

performing a backward calculation; and

repeating at least the forward calculation to extract each information bit of the set of information bits.

12. The method of claim 10 , wherein performing the plurality of forward calculations and backward calculations using the plurality of permutation layers separated by the neural network processing layers to retrieve the set of information bits includes:

performing the plurality of forward calculations and backward calculations; and

extracting the set of information bits from a result of the plurality of forward calculations and backward calculations.

13. The method of claim 10 , wherein each neural network processing layer includes a single neural network that accepts an entirety of the vector of input values.

14. The method of claim 10 , wherein each neural network processing layer includes a plurality of neural networks that each accepts a subset of the vector of input values.

15. The method of claim 14 , wherein for a given neural network processing layer, weights of each neural network in the plurality of neural networks are the same.

16. The method of claim 14 , wherein each neural network of the plurality of neural networks accepts a pair of input values from the vector of input values as input.

17. The method of claim 10 , wherein at least one neural network processing layer of the neural network processing layers uses SeLU activation.

18. The method of claim 10 , further comprising removing one or more zero values from an output of the plurality of permutation layers separated by the neural network processing layers to retrieve the set of information bits.

19. The method of claim 10 , wherein the codeword is a real-valued vector.

20. A method of reliable wireless reception of a set of information bits, the method comprising:

wirelessly receiving a codeword; and

decoding a set of information bits from the codeword;

wherein decoding the set of information bits from the codeword comprises a method as recited in claim 10 .

Assignments (3)

Continuity (2)

References Cited (74)