BR112020014657A2 - Feedback de configuração de formação de rede neural para comunicações sem fio - Google Patents
Feedback de configuração de formação de rede neural para comunicações sem fioInfo
- Publication number
- BR112020014657A2 BR112020014657A2 BR112020014657A BR112020014657A BR112020014657A2 BR 112020014657 A2 BR112020014657 A2 BR 112020014657A2 BR 112020014657 A BR112020014657 A BR 112020014657A BR 112020014657 A BR112020014657 A BR 112020014657A BR 112020014657 A2 BR112020014657 A2 BR 112020014657A2
- Authority
- BR
- Brazil
- Prior art keywords
- neural network
- network formation
- wireless communications
- configuration feedback
- deep neural
- Prior art date
Links
- 238000013528 artificial neural network Methods 0.000 title abstract 12
- 230000015572 biosynthetic process Effects 0.000 title abstract 7
- 238000000034 method Methods 0.000 abstract 1
Classifications
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/16—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks using machine learning or artificial intelligence
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/12—Arrangements for detecting or preventing errors in the information received by using return channel
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L1/00—Arrangements for detecting or preventing errors in the information received
- H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
- H04L1/0015—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy
- H04L1/0016—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy involving special memory structures, e.g. look-up tables
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
- H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver
- H04L5/0051—Allocation of pilot signals, i.e. of signals known to the receiver of dedicated pilots, i.e. pilots destined for a single user or terminal
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/08—Testing, supervising or monitoring using real traffic
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/044—Recurrent networks, e.g. Hopfield networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L5/00—Arrangements affording multiple use of the transmission path
- H04L5/003—Arrangements for allocating sub-channels of the transmission path
- H04L5/0048—Allocation of pilot signals, i.e. of signals known to the receiver
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Computer Networks & Wireless Communication (AREA)
- Evolutionary Computation (AREA)
- Artificial Intelligence (AREA)
- Software Systems (AREA)
- Computing Systems (AREA)
- Biomedical Technology (AREA)
- General Health & Medical Sciences (AREA)
- Molecular Biology (AREA)
- Computational Linguistics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Physics (AREA)
- Biophysics (AREA)
- Data Mining & Analysis (AREA)
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Medical Informatics (AREA)
- Databases & Information Systems (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Quality & Reliability (AREA)
- Mobile Radio Communication Systems (AREA)
Abstract
feedback de configuração de formação de rede neural para comunicações sem fio. técnicas e aparelhos são descritos para feedback de configuração de formação de rede neural para comunicações sem fio. uma entidade de rede (estação base 120, servidor de rede principal 302) determina um conjunto (conjuntos 2002, 2104) de sinais de referência de rede neural profunda para enviar em um canal físico para medir o desempenho de redes neurais profundas e/ou um conjunto de configurações de formação de rede neural (conjuntos 2004, 2106). a entidade de rede comunica indicações (indicações 2030, 2102) do conjunto de configurações de formação de rede neural e o conjunto de sinais de referência de rede neural profunda a um equipamento de usuário (ue 110). a entidade de rede inicia a transmissão de cada sinal de referência de rede neural profunda do conjunto, e direciona o equipamento de usuário para medir (saídas 2032, 2034, 2036, 2124, 2128, 2132) o desempenho de um conjunto de redes neurais profundas formadas usando o conjunto de configurações de formação de rede neural, e seleciona uma do conjunto de configurações de formação de rede neural.
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
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PCT/US2019/049566 WO2021045748A1 (en) | 2019-09-04 | 2019-09-04 | Neural network formation configuration feedback for wireless communications |
Publications (1)
Publication Number | Publication Date |
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BR112020014657A2 true BR112020014657A2 (pt) | 2022-03-22 |
Family
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Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
BR112020014657A BR112020014657A2 (pt) | 2019-09-04 | 2019-09-04 | Feedback de configuração de formação de rede neural para comunicações sem fio |
Country Status (6)
Country | Link |
---|---|
US (1) | US11397893B2 (pt) |
EP (1) | EP3808024B1 (pt) |
CN (1) | CN112997435B (pt) |
BR (1) | BR112020014657A2 (pt) |
RU (1) | RU2739483C1 (pt) |
WO (1) | WO2021045748A1 (pt) |
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US20230259789A1 (en) | 2020-07-10 | 2023-08-17 | Google Llc | Federated learning for deep neural networks in a wireless communication system |
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2019
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- 2019-09-04 CN CN201980008572.5A patent/CN112997435B/zh active Active
- 2019-09-04 BR BR112020014657A patent/BR112020014657A2/pt unknown
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- 2019-09-04 RU RU2020123400A patent/RU2739483C1/ru active
- 2019-09-04 US US16/957,367 patent/US11397893B2/en active Active
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CN112997435B (zh) | 2024-04-09 |
WO2021045748A1 (en) | 2021-03-11 |
US11397893B2 (en) | 2022-07-26 |
RU2739483C1 (ru) | 2020-12-24 |
US20210064996A1 (en) | 2021-03-04 |
CN112997435A (zh) | 2021-06-18 |
EP3808024B1 (en) | 2022-03-16 |
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