PATENT CLAIM ANALYSIS

Application Number: 16026811
Application Type: Utility
Filing Date: 2018-07
Publication Date: 2019-06
Patent Classification: ["714", "776000"]

Abstract:
Devices and methods described herein decode a sequence of coded symbols by guessing noise. In various embodiments, noise sequences are ordered, either during system initialization or on a periodic basis. Then, determining a codeword includes iteratively guessing a new noise sequence, removing its effect from received data symbols (e.g. by subtracting or using some other method of operational inversion), and checking whether the resulting data are a codeword using a codebook membership function. This process is deterministic, has bounded complexity, asymptotically achieves channel capacity as in convolutional codes, but has the decoding speed of a block code. In some embodiments, the decoder tests a bounded number of noise sequences, abandoning the search and declaring an erasure after these sequences are exhausted. Abandonment decoding nevertheless approximates maximum likelihood decoding within a tolerable bound and achieves channel capacity when the abandonment threshold is chosen appropriately.

Claim (Index 31):
A method according to  claim 30 , wherein obtaining the termination condition further comprises determining that the repetition count has reached at least a second threshold that is a function of a codebook rate, an estimated noise property, or both.

Metadata:
- Claim Count in Document: 59.0
- Percentile: 95.0
- Lexical Diversity: 1.57282
- Patent Class: 714.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16026822', '12411066', '10329864', '15236066', '15593402']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.2619774803551549
- 35 USC 102 Novelty (BERT): 0.5540082531086183
- Combined Prediction Score: 0.2911805576305012
- Mean Citation Score: 227.396804
- Max Citation Score: 420.35922
- Similarity Product: 323.00302808601015

Labels:
- Claim Label 101: 1
- Claim Label 102: 1
- Claim Label 103: 1
- Claim Label 112: 0
- Combined Label: 1
- Label 101 Adjusted: 1

Dataset: test