Nec Laboratories America, Inc Patent Portfolio Statistics

Nec Laboratories America, Inc.

Profile Summary

This article summarizes the perfomance of the assignee in the recent years. The overall statistics for this portfolio help to analyze the areas where the assignee is performing well. The filing trend, perfomance across the tech centers and the perfomance of the recent applications has been mentioned below. All the stats are calculated based on the perfomance in USPTO.

How does the overall patent portfolio of Nec Laboratories America, Inc. look like?

Assignee Art Units
Total Applications: 1,809 1,420,806
Granted Patents: 1,301 844,266
Grant Index 82.45% 79.63%
Abandoned/Rejected Applications: 277 (17.55%) 216,028 (20.37%)
In-Process Applications: 224 360,512
Average Grant Time: 2.58 Years 2.99 Years
Average Office Actions: 1.1 1.72

Which Technology Area Nec Laboratories America, Inc. is filing most patents in? (Last 10 years)

Art Unit Definition Total Applications
Opap Parked GAU 133
2636 Digital and Optical Communications 106
2637 Digital and Optical Communications 51
2613 Computer Graphic Processing, 3D Animation, Display Color Attribute, Object Processing, Hardware and Memory 43
2129 AI & Simulation/Modeling 40

How many patents are Nec Laboratories America, Inc. filing every year?

Year Total Applications Predicted
2022 0* 671
2021 110* 583
2020 115 603
2019 91 91
2018 143
2017 121
2016 86
2015 100
2014 135
2013 104

*The drop in the number of applications filed in last two years compared to previous years is because applications can take up to 18 months to get published

Recently filed patent applications of Nec Laboratories America, Inc. in USPTO?

Publication number: US20220187121A1
Application number: 17/548,581

Aspects of the present disclosure describe systems, methods and structures for coherent distributed sensing that employs a moving average method among locations along a sensing fiber employing a user configured number of taps that involves location grouping and a group's internal phase alignment followed by an inter-group phase alignment and combining. Our method employs two steps of rotation to achieve the alignment: intra-group rotation and inter-group rotation to align the phase of all participating sensing fiber locations.

Publication date: 2022-06-16
Applicant: Nec Laboratories America, Inc.
Inventors: Ezra Ip

Publication number: US20220182170A1
Application number: 17/543,616

Aspects of the present disclosure describe systems, methods. and structures directed to an integrated 3-way branching unit switch module suitable for undersea application.

Publication date: 2022-06-09
Applicant: Nec Laboratories America, Inc.
Inventors: Fatih Yaman

Publication number: US20220173808A1
Application number: 17/540,132

Aspects of the present disclosure describe systems, methods. and structures in which guided acoustic Brillouin (GAWBS) noise is measured using a homodyne measurement technique and demonstrated using a number of optical fibers, such fibers being commonly used in contemporary optical communications systems. The measurements are made with single spans and determined to be consistent with separate multi-span long-distance measurements. Additionally, a technique for preparing an optical fiber exhibiting superior GAWBS noise characteristics by reducing coherence length of the optical fiber by spinning the fiber at a high rate during the drawing process such that birefringence coherence length is reduced.

Publication date: 2022-06-02
Applicant: Nec Laboratories America, Inc.
Inventors: Inoue Takanori

How are Nec Laboratories America, Inc.’s applications performing in USPTO?

Application Number Title Status Art Unit Examiner
17/548,581 Spatial Averaging Method For Coherent Distributed Acoustic Sensing OPAP Central, Docket
17/543,616 Integrated 3-Way Branching Unit Switch Module Having Small Footprint OPAP Central, Docket
17/540,132 Optical Fiber Exhibiting Low Guided Acoustic Brillouin Scattering (Gawbs) Noise And Measurement Thereof OPAP Central, Docket
17/529,622 Information Theory Guided Sequential Representation Disentanglement And Data Generation OPAP Central, Docket
17/528,394 Unsupervised Document Representation Learning Via Contrastive Augmentation OPAP Central, Docket