4 citations · 4 across the 7 of their papers we have counts for
7 papers
Deep Learning-based Data-aided Activity Detection with Extraction Network in Grant-free Sparse Code Multiple Access Systems
Minsig Han, Ameha T. Abebe, Chung G. Kang
This letter proposes a deep learning-based data-aided active user detection network (D-AUDN) for grant-free sparse code multiple access (SCMA) systems that leverages both SCMA code…
On the Performance of Deep Learning-based Data-aided Active User Detection for GF-SCMA System
Minsig Han, Ameha Tsegaye Abebe, Chung G. Kang
The recent works on a deep learning (DL)-based joint design of preamble set for the transmitters and data-aided active user detection (AUD) in the receiver has demonstrated a signi…
DRL-based Distributed Resource Allocation for Edge Computing in Cell-Free Massive MIMO Network
Fitsum Debebe Tilahun, Ameha Tsegaye Abebe, Chung G. Kang
In this paper, with the aim of addressing the stringent computing and quality-of-service (QoS) requirements of recently introduced advanced multimedia services, we consider a cell-…
Data-aided Active User Detection with a User Activity Extraction Network for Grant-free SCMA Systems
Minsig Han, Ameha T. Abebe, Chung G. Kang
In grant-free sparse code multiple access (GF-SCMA) system, active user detection (AUD) is a major performance bottleneck as it involves complex combinatorial problem, which makes…
Multi-Agent Reinforcement Learning for Distributed Joint Communication and Computing Resource Allocation over Cell-Free Massive MIMO-enabled Mobile Edge Computing Network
Fitsum Debebe Tilahun, Ameha Tsegaye Abebe, Chung G. Kang
To support the newly introduced multimedia services with ultra-low latency and extensive computation requirements, resource-constrained end user devices should utilize the ubiquito…
Deep Learning-based Codebook Design for Code-domain Non-Orthogonal Multiple Access Approaching Single-User Bit Error Rate Performance
Minsig Han, Hanchang Seo, Ameha Tsegaye Abebe +1
A general form of codebook design for code-domain non-orthogonal multiple access (CD-NOMA) can be considered equivalent to an autoencoder (AE)-based constellation design for multi-…
Multi-sequence Spreading Random Access (MSRA) for Compressive Sensing-based Grant-free Communication
Ameha Tsegaye Abebe, Chung G. Kang
The performance of grant-free random access (GF-RA) is limited by the number of accessible random access resources (RRs) due to the absence of collision resolution. Compressive sen…