PATENT CLAIM ANALYSIS

Application Number: 16233444
Application Type: Utility
Filing Date: 2018-12
Publication Date: 2019-05
Patent Classification: ["375", "267000"]

Abstract:
A method for determining a precoding matrix indicator, user equipment, and a base station are disclosed in embodiments of the present invention. The method includes: receiving a first reference signal set sent by a base station, where the first reference signal set is associated with a user equipment-specific matrix or matrix set; selecting a precoding matrix based on the first reference signal set, where the precoding matrix is a function of the user equipment-specific matrix or matrix set; and sending a precoding matrix indicator to the base station, where the precoding matrix indicator corresponds to the selected precoding matrix. In the embodiments of the present invention, CSI feedback precision can be improved without excessively increasing feedback overhead, thereby improving system performance.

Claim (Index 31):
The apparatus according to  claim 27 , wherein the m th  column vector a m  of the matrix A is a discrete Fourier transformation DFT vector, the DFT vector a m  satisfies: a m = [ e j \ue89e \ue89e 2 \ue89e \u03c0 \u00b7 0 \u00b7 m N A e j \ue89e \ue89e 2 \ue89e \u03c0 \u00b7 1 \u00b7 m N A \u2026 e j \ue89e \ue89e 2 \ue89e \u03c0 \u00b7 ( M A - 1 ) \u00b7 m N A ] T , and wherein [ ] T  denotes a matrix transpose, M A  and N A  are positive integers, and N A <N C .

Metadata:
- Claim Count in Document: 10.0
- Percentile: 98.0
- Lexical Diversity: 2.12698
- Patent Class: 375.0
- Transitional Phrase Type: none
- Component Type: 0
- Foreign Priority: False
- Related Applications: ['16107653', '15951153', '15950820', '14936092', '14937392']

Analysis Scores:
- 35 USC 101 Eligibility (BERT): 0.5936530771073323
- 35 USC 102 Novelty (BERT): 0.6164906413743377
- Combined Prediction Score: 0.5959368335340328
- Mean Citation Score: 519.931026
- Max Citation Score: 580.7644
- Similarity Product: 491.2361700298786

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