no code implementations • 12 Mar 2024 • Junyong Shin, Yujin Kang, Yo-Seb Jeon
In this method, the magnitude of the latent vector is quantized using a non-uniform scalar codebook with a proper transformation function, while the direction of the latent vector is quantized using a trainable Grassmannian codebook.
no code implementations • 12 Mar 2024 • Yongjeong Oh, Jaehong Jo, Byonghyo Shim, Yo-Seb Jeon
The third framework is designed to accommodate the non-coherent scheme involving a small number of data bits, which simultaneously performs AD and DD.
no code implementations • 14 Nov 2023 • Joohyuk Park, Yongjeong Oh, Seonjung Kim, Yo-Seb Jeon
In semantic communication systems with digital modulation and demodulation, robust design of JSCC encoder and decoder becomes challenging not only due to the unpredictable dynamics of channel conditions but also due to diverse modulation orders.
no code implementations • 20 Jul 2023 • Jaewon Yun, Yongjeong Oh, Yo-Seb Jeon, H. Vincent Poor
Moreover, an error feedback strategy is introduced to compensate for both compression and reconstruction errors.
no code implementations • 20 Jul 2023 • Yongjeong Oh, Jaeho Lee, Christopher G. Brinton, Yo-Seb Jeon
In the second strategy, the non-dropped intermediate feature and gradient vectors are quantized using adaptive quantization levels determined based on the ranges of the vectors.
no code implementations • 8 Jun 2023 • Jinman Kwon, Seunghyeon Jeon, Yo-Seb Jeon, H. Vincent Poor
By using the outputs of coarse data detection as noisy training data, the model-driven method avoids the need for additional training overhead beyond traditional pilot overhead for channel estimation.
1 code implementation • 30 May 2022 • Moon Jeong Park, Jungseul Ok, Yo-Seb Jeon, Dongwoo Kim
There are two major limitations in the supervised approaches: a) a model needs to be retrained from scratch when new train symbols come to adapt to a new channel status, and b) the length of the training symbols needs to be longer than a certain threshold to make the model generalize well on unseen symbols.
no code implementations • 3 Apr 2022 • Tae-Kyoung Kim, Yo-Seb Jeon, Jun Li, Nima Tavangaran, H. Vincent Poor
Data-aided channel estimation is a promising solution to improve channel estimation accuracy by exploiting data symbols as pilot signals for updating an initial channel estimate.
no code implementations • 30 Nov 2021 • Yongjeong Oh, Namyoon Lee, Yo-Seb Jeon, H. Vincent Poor
We also present a low-complexity approach for the gradient reconstruction.
no code implementations • 28 Jan 2021 • Kang Wei, Jun Li, Ming Ding, Chuan Ma, Yo-Seb Jeon, H. Vincent Poor
An attacker in FL may control a number of participant clients, and purposely craft the uploaded model parameters to manipulate system outputs, namely, model poisoning (MP).
no code implementations • 18 Mar 2020 • Yo-Seb Jeon, Mohammad Mohammadi Amiri, Jun Li, H. Vincent Poor
One major challenge in system design is to reconstruct local gradient vectors accurately at the central server, which are computed-and-sent from the wireless devices.
no code implementations • 29 Mar 2019 • Yo-Seb Jeon, Namyoon Lee, H. Vincent Poor
The key idea is to exploit input-output samples obtained from data detection, to compensate the mismatch in the likelihood function.