19 citations · 74 across the 31 of their papers we have counts for
32 papers
Communication-Efficient Hybrid Language Model via Uncertainty-Aware Opportunistic and Compressed Transmission
Seungeun Oh, Jinhyuk Kim, Jihong Park +4
To support emerging language-based applications using dispersed and heterogeneous computing resources, the hybrid language model (HLM) offers a promising architecture, where an on-…
Uncertainty-Aware Hybrid Inference with On-Device Small and Remote Large Language Models
Seungeun Oh, Jinhyuk Kim, Jihong Park +3
This paper studies a hybrid language model (HLM) architecture that integrates a small language model (SLM) operating on a mobile device with a large language model (LLM) hosted at…
Energy-Efficient Edge Learning via Joint Data Deepening-and-Prefetching
Sujin Kook, Won-Yong Shin, Seong-Lyun Kim +1
The vision of pervasive artificial intelligence (AI) services can be realized by training an AI model on time using real-time data collected by internet of things (IoT) devices. To…
Mobility-Induced Graph Learning for WiFi Positioning
Kyuwon Han, Seung Min Yu, Seong-Lyun Kim +1
A smartphone-based user mobility tracking could be effective in finding his/her location, while the unpredictable error therein due to low specification of built-in inertial measur…
Towards Semantic Communication Protocols for 6G: From Protocol Learning to Language-Oriented Approaches
Jihong Park, Seung-Woo Ko, Jinho Choi +2
The forthcoming 6G systems are expected to address a wide range of non-stationary tasks. This poses challenges to traditional medium access control (MAC) protocols that are static…
Semantics Alignment via Split Learning for Resilient Multi-User Semantic Communication
Jinhyuk Choi, Jihong Park, Seung-Woo Ko +3
Recent studies on semantic communication commonly rely on neural network (NN) based transceivers such as deep joint source and channel coding (DeepJSCC). Unlike traditional transce…
Enabling AI Quality Control via Feature Hierarchical Edge Inference
Jinhyuk Choi, Seong-Lyun Kim, Seung-Woo Ko
With the rise of edge computing, various AI services are expected to be available at a mobile side through the inference based on deep neural network (DNN) operated at the network…
Joint Data Deepening-and-Prefetching for Energy-Efficient Edge Learning
Sujin Kook, Won-Yong Shin, Seong-Lyun Kim +1
The vision of pervasive machine learning (ML) services can be realized by training an ML model on time using real-time data collected by internet of things (IoT) devices. To this e…
Over-the-Air Consensus for Distributed Vehicle Platooning Control (Extended version)
Jihoon Lee, Yonghoon Jang, Hansol Kim +2
A distributed control of vehicle platooning is referred to as distributed consensus (DC) since many autonomous vehicles (AVs) reach a consensus to move as one body with the same ve…
Towards Semantic Communication Protocols: A Probabilistic Logic Perspective
Sejin Seo, Jihong Park, Seung-Woo Ko +3
Classical medium access control (MAC) protocols are interpretable, yet their task-agnostic control signaling messages (CMs) are ill-suited for emerging mission-critical application…
Combinatorial Data Augmentation: A Key Enabler to Bridge Geometry- and Data-Driven WiFi Positioning
Seung Min Yu, Jihong Park, Seung-Woo Ko
Due to the emergence of various wireless sensing technologies, numerous positioning algorithms have been introduced in the literature, categorized into \emph{geometry-driven positi…
Communication-Efficient and Personalized Federated Lottery Ticket Learning
Sejin Seo, Seung-Woo Ko, Jihong Park +2
The lottery ticket hypothesis (LTH) claims that a deep neural network (i.e., ground network) contains a number of subnetworks (i.e., winning tickets), each of which exhibiting iden…
Exploiting User Mobility for WiFi RTT Positioning: A Geometric Approach
Kyuwon Han, Seung Min Yu, Seong-Lyun Kim +1
Recently, round-trip time (RTT) measured by a fine-timing measurement protocol has received great attention in the area of WiFi positioning. It provides an acceptable ranging accur…
Cooperative Multi-Point Vehicular Positioning Using Millimeter-Wave Surface Reflection (Extended version)
Zezhong Zhang, Seung-Woo Ko, Rui Wang +1
Multi-point vehicular positioning is one essential operation for autonomous vehicles. However, the state-of-the-art positioning technologies, relying on reflected signals from a ta…
Understanding Uncertainty of Edge Computing: New Principle and Design Approach
Sejin Seo, Sang Won Choi, Sujin Kook +2
Due to the edge's position between the cloud and the users, and the recent surge of deep neural network (DNN) applications, edge computing brings about uncertainties that must be u…
Random Access with Opportunity Detection in Wireless Networks
Jinho Choi, Seung-Woo Ko, Koji Yamamoto +1
This letter proposes a novel random medium access control (MAC) based on a transmission opportunity prediction, which can be measured in a form of a conditional success probability…
V2X-Based Vehicular Positioning: Opportunities, Challenges, and Future Directions
Seung-Woo Ko, Hyukjin Chae, Kaifeng Han +3
Vehicle-to-Everything (V2X) will create many new opportunities in the area of wireless communications, while its feasibility on enabling vehicular positioning has not been explored…
Joint Frequency-and-Phase Modulation for Backscatter-Tag Assisted Vehicular Positioning
Kaifeng Han, Seung-Woo Ko, Seungmin Lee +2
Autonomous driving (auto-driving) has been becoming a killer technology for next generation vehicles, whereas some fatal accidents grow concerns about its safety. A fundamental fun…
Realizing Multi-Point Vehicular Positioning via Millimeter-wave Transmission
Zezhong Zhang, Seung-Woo Ko, Rui Wang +1
Multi-point detection of the full-scale environment is an important issue in autonomous driving. The state-of-the-art positioning technologies (such as RADAR and LIDAR) are incapab…
Sensing Hidden Vehicles by Exploiting Multi-Path V2V Transmission
Kaifeng Han, Seung-Woo Ko, Hyukjin Chae +2
This paper presents a technology of sensing hidden vehicles by exploiting multi-path vehicle-to-vehicle (V2V) communication. This overcomes the limitation of existing RADAR technol…
Hidden Vehicle Sensing via Asynchronous V2V Transmission: A Multi-Path-Geometry Approach
Kaifeng Han, Seung-Woo Ko, Hyukjin Chae +2
Accurate vehicular sensing is a basic and important operation in autonomous driving. Unfortunately, the existing techniques have their own limitations. For instance, the communicat…
Sense-and-Predict: Harnessing Spatial Interference Correlation for Cognitive Radio Networks
Seunghwan Kim, Han Cha, Jeemin Kim +2
Cognitive radio (CR) is a key enabler realizing future networks to achieve higher spectral efficiency by allowing spectrum sharing between different wireless networks. It is import…
Opportunism in Dynamic Spectrum Access for 5G: A Concept and Its Application to Duplexing
Jeemin Kim, Soo-Min Kim, Han Cha +4
With the envisioned massive Internet-of-Things (IoT) era, one of the challenges for 5G wireless systems will be handling the unprecedented spectrum crunch. A potential solution has…
Enhancing TCP End-to-End Performance in Millimeter-Wave Communications
Minho Kim, Seung-Woo Ko, Seong-Lyun Kim
Recently, millimeter-wave (mmWave) communications have received great attention due to the availability of large spectrum resources. Nevertheless, their impact on TCP performance h…