12 papers
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…
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.…
Resource-Constrained Decentralized Federated Learning via Personalized Event-Triggering
Shahryar Zehtabi, Seyyedali Hosseinalipour, Christopher G. Brinton
Federated learning (FL) is a popular technique for distributing machine learning (ML) across a set of edge devices. In this paper, we study fully decentralized FL, where in additio…
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…
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…
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…