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Methods and Procedures for Synchronization and Over-the-Air Computation
Reference #: 01615 The University of South Carolina is offering licensing opportunities for Methods and Procedures for Synchronization and Over-the-Air Computation Background: Over-the-air computation (OAC) reduces the communication latency that linearly increases with the number of devices in a wireless network for machine learning applications....
Published: 2/28/2024
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Inventor(s):
Alphan Sahin
Keywords(s):
federated learning
,
non-coherent computation
,
over-the-air computation
,
software-defined radios
,
sychronization
Category(s):
Software and Computing
,
Engineering and Physical Sciences
Over-the-Air Computation Methods Based on Balanced Number Systems for FEEL
Reference #: 01612 The University of South Carolina is offering licensing opportunities for Over-the-Air Computation Methods Based on Balanced Number Systems for FEEL Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 10/24/2022
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Inventor(s):
Alphan Sahin
Keywords(s):
federated learning
,
non-coherent computation
,
over-the-air computation
,
quantization
,
signed-digit number system
Category(s):
Software and Computing
,
Engineering and Physical Sciences
Methods for Long-Range Federated Edge Learning with Chirp-Based Over-the-Air Computation
Reference #: 01574 The University of South Carolina is offering licensing opportunities for Methods for Long-Range Federated Edge Learning with Chirp-Based Over-the-Air Computation Background: Federated edge learning (FEEL) deploys federated learning (FL) over a wireless network, in which many edge devices (EDs) participate in training using locally...
Published: 1/3/2023
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Inventor(s):
Safi Shams Muhtasimul Hoque
,
Alphan Sahin
Keywords(s):
chirp
,
DFT-s-OFDM
,
Distributed learning
,
federated edge learning
,
LoRa
,
orthogonal frequency division multiplexing
,
over-the-air computation
,
peak-to-mean envelope power ratio
,
pulse-position modulation
Category(s):
Engineering and Physical Sciences
,
Software and Computing
Methods for Multi-cell Over-the-Air Computation for Distributed Learning
Reference #: 01573 The University of South Carolina is offering licensing opportunities for Methods for Multi-cell Over-the-Air Computation for Distributed Learning Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 5/9/2023
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Inventor(s):
Mohammad Hassan Adeli
,
Alphan Sahin
Keywords(s):
Distributed learning
,
federated edge learning
,
frequency-shift keying
,
orthogonal frequency division multiplexing
,
over-the-air computation
,
peak-to-mean envelope power ratio
Category(s):
Engineering and Physical Sciences
,
Software and Computing
Methods for Reliable Over-the-Air Computation with Pulses for Distributed Learning
Reference #: 01541 The University of South Carolina is offering licensing opportunities for Methods for Reliable Over-the-Air Computation with Pulses for Distributed Learning Background: Federated edge learning (FEEL) is an implementation of federated learning (FL) over a wireless network to train a model by using the local data at the edge devices...
Published: 9/3/2022
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Inventor(s):
Alphan Sahin
,
Everette Bryson
,
Safi Shams Muhtasimul Hoque
Keywords(s):
DFT-s-OFDM
,
Distributed learning
,
federated edge learning
,
orthogonal frequency division multiplexing
,
over-the-air computation
,
peak-to-mean envelope power ratio
,
pulse-position modulation
,
SC-FDE
Category(s):
Software and Computing
,
Engineering and Physical Sciences
Methods for Reliable Over-the-Air Computation and Federated Edge Learning
Reference #: 01538 The University of South Carolina is offering licensing opportunities for Methods for Reliable Over-the-Air Computation and Federated Edge Learning Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 9/3/2022
|
Inventor(s):
Alphan Sahin
,
Everette Bryson
,
Safi Shams Muhtasimul Hoque
Keywords(s):
Distributed learning
,
federated edge learning
,
frequency-shift keying
,
orthogonal frequency division multiplexing
,
over-the-air computation
,
peak-to-mean envelope power ratio
Category(s):
Engineering and Physical Sciences
,
Software and Computing
Methods for Encoding and Decoding based on Partitioned Complementary Sequences
Reference #: 01512 The University of South Carolina is offering licensing opportunities for Methods for Encoding and Decoding based on Partitioned Complementary Sequences Background: Orthogonal frequency division multiplexing (OFDM) waveform utilized in 4G, 5G, and Wi-Fi has peaky signal characteristics. Hence, the waveform is often distorted under...
Published: 9/3/2022
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Inventor(s):
Alphan Sahin
Keywords(s):
low PAPR
,
Partitioned complementary sequences
,
Reed-Muller code
Category(s):
Engineering and Physical Sciences
Methods for Wideband Index Modulation Based on Chirp Signals
Reference #: 01476 The University of South Carolina is offering licensing opportunities for Methods for Wideband Index Modulation based on Chirp Signals Background: Chirp can provide robustness against distortions due to the non-linear components in a radio-frequency chain, for example a non-linear power amplifier. They also provide good correlation...
Published: 9/3/2022
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Inventor(s):
Alphan Sahin
,
Safi Shams Muhtasimul Hoque
Keywords(s):
chirp signals
,
Complementary sequences
,
DFT-spread OFDM
,
SC-FDMA
Category(s):
Engineering and Physical Sciences
,
Software and Computing
Methods for Non-linear Distortion Immune End-to-End Learning with Autoencoder-OFDM
Reference #: 01441 The University of South Carolina is offering licensing opportunities for Methods for Non-linear Distortion Immune End-to-End Learning with Autoencoder-OFDM1 Background: AI-based communication systems utilize machine learning modules (e.g., deep learning) to replace the functionality of the highly engineered blocks (e.g., coding,...
Published: 9/4/2022
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Inventor(s):
David Matolak
,
Alphan Sahin
Keywords(s):
Autoencoder
,
Complementary sequences
,
machine learning
,
OFDM
,
PAPR
Category(s):
Engineering and Physical Sciences
,
Software and Computing
Methods for Reliable Chirp Transmissions
Reference #: 01439 The University of South Carolina is offering licensing opportunities for Methods for Reliable Chirp Transmissions and Multiplexing Background: To increase the reliability and security of communication systems the communication link must be established over multiple bands, e.g., L-Band (1-2 GHz) and C-Band (4-8 GHz) for aeronautical...
Published: 9/4/2022
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Inventor(s):
David Matolak
,
Alphan Sahin
,
Nozhan Hosseini
Keywords(s):
coded orthogonal chirp division multiplexing
,
Complementary sequence-based chirp spread spectrum
,
shift encoders
,
trajectory encoding with multi-DFT clusters
Category(s):
Engineering and Physical Sciences
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