most citedDynamic and Robust Sensor Selection Strategies for Wireless Positioning with TOA/RSS Measurement

9 citations · 12 across the 2 of their papers we have counts for

collaborators

5 papers

eess.SP20269 cited

Dynamic and Robust Sensor Selection Strategies for Wireless Positioning with TOA/RSS Measurement

Myeung Suk Oh, Seyyedali Hosseinalipour, Taejoon Kim +3

Emerging wireless applications are requiring ever more accurate location-positioning from sensor measurements. In this paper, we develop sensor selection strategies for 3D wireless…

eess.SP20263 cited

Channel Estimation via Successive Denoising in MIMO OFDM Systems: A Reinforcement Learning Approach

Myeung Suk Oh, Seyyedali Hosseinalipour, Taejoon Kim +2

In general, reliable communication via multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) requires accurate channel estimation at the receiver.…

eess.SP2025

Minimum Description Feature Selection for Complexity Reduction in Machine Learning-based Wireless Positioning

Myeung Suk Oh, Anindya Bijoy Das, Taejoon Kim +2

Recently, deep learning approaches have provided solutions to difficult problems in wireless positioning (WP). Although these WP algorithms have attained excellent and consistent p…

cs.LG2025

Complexity Reduction in Machine Learning-Based Wireless Positioning: Minimum Description Features

Myeung Suk Oh, Anindya Bijoy Das, Taejoon Kim +2

A recent line of research has been investigating deep learning approaches to wireless positioning (WP). Although these WP algorithms have demonstrated high accuracy and robust perf…

eess.SP2025

A Decentralized Pilot Assignment Algorithm for Scalable O-RAN Cell-Free Massive MIMO

Myeung Suk Oh, Anindya Bijoy Das, Seyyedali Hosseinalipour +3

Radio access networks (RANs) in monolithic architectures have limited adaptability to supporting different network scenarios. Recently, open-RAN (O-RAN) techniques have begun addin…