Search Results for author:
Found 3 papers, 0 papers with code
Time-based vs. Fingerprinting-based Positioning Using Artificial Neural Networks
When comparing time-based and fingerprinting schemes using ANNs, we show that the favorable method in terms of positioning accuracy is different for different environments, where the accuracy is affected not only by the radio propagation conditions but also the density and distribution of reference user locations used for fingerprinting.
Time of Arrival Error Estimation for Positioning Using Convolutional Neural Networks
Wireless high-accuracy positioning has recently attracted growing research interest due to diversified nature of applications such as industrial asset tracking, autonomous driving, process automation, and many more.
Matching Pursuit Based Scheduling for Over-the-Air Federated Learning
Compared to the state-of-the-art, the proposed scheme poses a drastically lower computational load on the system: For $K$ devices and $N$ antennas at the parameter server, the benchmark complexity scales with $\left(N^2+K\right)^3 + N^6$ while the complexity of the proposed scheme scales with $K^p N^q$ for some $0 < p, q \leq 2$.
