IP Library › Granted Patent US 11,489,624
Granted Patent B2
US 11,489,624 · App. 17/688,718 · Granted Nov 1, 2022

Error correction in network packets using lookup tables

Inventors: RaviKiran Gopalan (Cupertino, CA); Anand Chandrasekher (Saratoga, CA); Yihan Jiang (Cupertino, CA); Arman Rahimzamani (San Jose, CA)
Assignee: Aira Technologies, Inc.
H04L1/0061H04L1/0084H04L1/18
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Quick Facts
Patent No.
US 11,489,624
App. No.
17/688,718
Granted
Nov 1, 2022
Kind
B2
Abstract

Error correction in network packets using lookup tables are disclosed herein. The method can include extracting soft information from copies of a network packet, using the soft information to select positions in a payload of the network packet with uncertain values of bits, changing values at the positions to a combination of values to obtain a modified payload of the network packet, and calculating the CRC for the modified payload. When the modified payload matches an error detection code in the network packet, errors in the payload are corrected.

Claims (16)

1. A system comprising:

a processor; and

a memory for storing instructions, the processor executing the instructions to:

receive copies of a network packet;

extract soft information from the copies of the network packet;

use the soft information to select K positions in a payload of the network packet with uncertain values of bits;

select the K positions having largest levels of uncertainty;

change the uncertain values at the K positions to selected combination of values to obtain a modified payload of the network packet; and

calculate an error detection code for the modified payload, wherein when the modified payload matches the error detection code in the network packet, errors in the payload are corrected.

2. The system according to claim 1 , wherein the soft information may include expected values for bits in positions of the payload of the network packet.

3. The system according to claim 2 , wherein extracting soft information includes obtaining the expected values using a machine learning model.

4. The system according to claim 3 , wherein the machine learning model evaluates values of bits at position j in all the copies of the network packet and values of bits in positions neighboring to j in the copies of the network packet.

5. The system according to claim 4 , further comprising determining levels of uncertainty for the positions of bits in the payload, wherein a level of uncertainty for the position j can be found as minimum between a distance of an expected value at the position j from 0 and a distance of the expected value at the position j from 1.

6. The system according to claim 5 , further comprising selecting a combination of values of K bits from 2 K possible combinations of values of bits at selected K positions.

7. The system according to claim 6 , wherein when the modified payload does not match the error detection code in the network packet, the processor is further configured to determine that all possible combinations of values of K bits have been selected and tested, and selecting a next combination when all the possible combinations have not been selected and tested.

8. The system according to claim 7 , further comprising requesting that the network packet be retransmitted when the network packet cannot be corrected.

Assignments (3)
CHANGE OF ADDRESS Recorded Jul 20, 2023
From: AIRA TECHNOLOGIES, INC.
To: AIRA TECHNOLOGIES, INC.
Reel/Frame 064353/0359 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 8, 2022
From: GOPALAN, RAVIKIRAN; CHANDRASEKHER, ANAND; JIANG, YIHAN
To: AIRA TECHNOLOGIES, INC.
Reel/Frame 059200/0615 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 8, 2022
From: RAHIMZAMANI, ARMAN
To: AIRA TECHNOLOGIES, INC.
Reel/Frame 059200/0685 →
Continuity (2)
Provisional Application 63158817 · Mar 9, 2021
Related Publication 20220294561A1 · Sep 15, 2022