Chirp-based majority vote computation for federated edge learning and distributed localization
In this study, we propose an over-the-air computation (OAC) scheme based on chirps to
detect the majority votes (MVs) in a wireless network for federated edge learning (FEEL) and …
detect the majority votes (MVs) in a wireless network for federated edge learning (FEEL) and …
Distributed learning over a wireless network with non-coherent majority vote computation
A Şahin - IEEE Transactions on Wireless Communications, 2023 - ieeexplore.ieee.org
In this study, we propose an over-the-air computation (OAC) scheme to calculate the
majority vote (MV) for federated edge learning (FEEL). With the proposed approach, edge …
majority vote (MV) for federated edge learning (FEEL). With the proposed approach, edge …
Distributed learning over a wireless network with FSK-based majority vote
In this study, we propose an over-the-air computation (AirComp) scheme for federated edge
learning (FEEL). The proposed scheme relies on the concept of distributed learning by …
learning (FEEL). The proposed scheme relies on the concept of distributed learning by …
Chirp-based over-the-air computation for power-efficient distributed localization
In this study, we propose an over-the-air computation (OAC) approach for power-efficient
localization in a sensor network. The proposed approach relies on a voting-based …
localization in a sensor network. The proposed approach relies on a voting-based …
Chirp-based over-the-air computation for long-range federated edge learning
In this study, we propose circularly-shifted chirp (CSC)-based majority vote (MV)(CSC-MV),
a power-efficient over-the-air computation (OAC) scheme, to achieve long-range federated …
a power-efficient over-the-air computation (OAC) scheme, to achieve long-range federated …
Multi-cell non-coherent over-the-air computation for federated edge learning
In this paper, we propose a framework where over-the-air computation (OAC) occurs in both
uplink (UL) and downlink (DL), sequentially, in a multi-cell environment to address the …
uplink (UL) and downlink (DL), sequentially, in a multi-cell environment to address the …
Machine learning for wideband localization
T Van Nguyen, Y Jeong, H Shin… - IEEE Journal on …, 2015 - ieeexplore.ieee.org
Wireless localization has a great importance in a variety of areas including commercial,
service, and military positioning and tracking systems. In harsh indoor environments, it is …
service, and military positioning and tracking systems. In harsh indoor environments, it is …
Federated learning-based localization with heterogeneous fingerprint database
Fingerprint-based localization plays an important role in indoor location-based services,
where the position information is usually collected in distributed clients and gathered in a …
where the position information is usually collected in distributed clients and gathered in a …
Over-the-air computation with DFT-spread OFDM for federated edge learning
In this study, we propose an over-the-air computation (AirComp) scheme for federated edge
learning (FEEL) without channel state information (CSI) at the edge devices (EDs) or the …
learning (FEEL) without channel state information (CSI) at the edge devices (EDs) or the …
Federated distillation based indoor localization for IoT networks
The federated distillation (FD) paradigm has been recently proposed as a promising
alternative to federated learning (FL), especially in wireless sensor networks with limited …
alternative to federated learning (FL), especially in wireless sensor networks with limited …