PATENT CLAIM ANALYSIS

Application Number: 15970324
Application Type: Utility
Filing Date: 2018-05
Publication Date: 2018-11
Patent Classification: ["706", "022000"]

Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for training and deploying machine-learned communication over radio frequency (RF) channels. One of the methods includes: determining first information; using an encoder machine-learning network to process the first information and generate a first RF signal for transmission through a communication channel; determining a second RF signal that represents the first RF signal having been altered by transmission through the communication channel; using a decoder machine-learning network to process the second RF signal and generate second information as a reconstruction of the first information; calculating a measure of distance between the second information and the first information; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on the measure of distance between the second information and the first information.

Claim (Index 7):
The method of  claim 6 , wherein the at least one channel-modeling layer represents at least one of (i) additive Gaussian thermal noise in the communication channel, (ii) delay spread caused by time-varying effects of the communication channel, (iii) phase noise caused by transmission and reception over the communication channel, or (iv) offsets in phase, frequency, or timing caused by transmission and reception over the communication channel.

Metadata:
- Claim Count in Document: 29.0
- Percentile: 93.0
- Lexical Diversity: 2.22059
- Patent Class: 706.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['15961454', '15961465', '15380399', '16304396', '15369849']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.4047351327728629
- 35 USC 102 Novelty (BERT): 0.5260209636309761
- Combined Prediction Score: 0.4168637158586742
- Mean Citation Score: 236.649754
- Max Citation Score: 341.5363200000001
- Similarity Product: 217.3138086902619

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

Dataset: test