no code implementations • 21 Apr 2024 • Myeung Suk Oh, Anindya Bijoy Das, Taejoon Kim, David J. Love, Christopher G. Brinton
In this work, we design a novel positioning neural network (P-NN) that utilizes the minimum description features to substantially reduce the complexity of deep learning-based WP.
no code implementations • 14 Feb 2024 • Myeung Suk Oh, Anindya Bijoy Das, Taejoon Kim, David J. Love, Christopher G. Brinton
A recent line of research has been investigating deep learning approaches to wireless positioning (WP).
no code implementations • 31 Dec 2023 • JungHoon Kim, Taejoon Kim, Anindya Bijoy Das, Seyyedali Hosseinalipour, David J. Love, Christopher G. Brinton
In this work, we aim to enhance and balance the communication reliability in GTWCs by minimizing the sum of error probabilities via joint design of encoders and decoders at the users.
no code implementations • 30 Apr 2023 • Myeung Suk Oh, Seyyedali Hosseinalipour, Taejoon Kim, David J. Love, James V. Krogmeier, Christopher G. Brinton
For dynamic sensor selection, two greedy selection strategies are proposed, each of which exploits properties revealed in the derived CRLB expressions.
no code implementations • 25 Apr 2023 • JungHoon Kim, Taejoon Kim, David Love, Christopher Brinton
The design of codes for feedback-enabled communications has been a long-standing open problem.
no code implementations • 12 Jan 2023 • Myeung Suk Oh, Anindya Bijoy Das, Seyyedali Hosseinalipour, Taejoon Kim, David J. Love, Christopher G. Brinton
Radio access networks (RANs) in monolithic architectures have limited adaptability to supporting different network scenarios.
no code implementations • 14 Dec 2022 • Dang Qua Nguyen, Taejoon Kim
In wideband sub-Terahertz (sub-THz) massive multiple-input multiple-output (MIMO) communication systems, the beam squint effect manifests as a substantial degradation in array gain.
no code implementations • 7 May 2022 • JungHoon Kim, Seyyedali Hosseinalipour, Andrew C. Marcum, Taejoon Kim, David J. Love, Christopher G. Brinton
Intelligent reflecting surfaces (IRS) consist of configurable meta-atoms, which can alter the wireless propagation environment through design of their reflection coefficients.
no code implementations • 31 Dec 2021 • Yiju Yang, Tianxiao Zhang, Guanyu Li, Taejoon Kim, Guanghui Wang
In this paper, we propose a dual-module network architecture that employs a domain discriminative feature module to encourage the domain invariant feature module to learn more domain invariant features.
no code implementations • 3 Dec 2021 • JungHoon Kim, Seyyedali Hosseinalipour, Andrew C. Marcum, Taejoon Kim, David J. Love, Christopher G. Brinton
We consider a practical setting where (i) the IRS reflection coefficients are achieved by adjusting tunable elements embedded in the meta-atoms, (ii) the IRS reflection coefficients are affected by the incident angles of the incoming signals, (iii) the IRS is deployed in multi-path, time-varying channels, and (iv) the feedback link from the base station to the IRS has a low data rate.
no code implementations • 4 Sep 2021 • Usman Sajid, Xiangyu Chen, Hasan Sajid, Taejoon Kim, Guanghui Wang
Crowd estimation is a very challenging problem.
1 code implementation • 2 Aug 2021 • Yiju Yang, Taejoon Kim, Guanghui Wang
In this paper, we propose to extend the structure to multiple classifiers to further boost its performance.
no code implementations • 11 Jul 2021 • Qiyou Duan, Hadi Ghauch, Taejoon Kim
To make our method more scalable to large-dimensional problems, we propose two acceleration schemes, namely, the eigenvalue decomposition (EVD) elimination strategy and an approximate EVD algorithm.
no code implementations • 25 Apr 2021 • Usman Sajid, Michael Chow, Jin Zhang, Taejoon Kim, Guanghui Wang
To address these issues, we propose a new multi-scale and encoder-based attention network for text recognition that performs the multi-scale FE and VA in parallel.
no code implementations • 25 Jan 2021 • Myeung Suk Oh, Seyyedali Hosseinalipour, Taejoon Kim, Christopher G. Brinton, David J. Love
Our methodology includes a new successive channel denoising process based on channel curvature computation, for which we obtain a channel curvature magnitude threshold to identify unreliable channel estimates.
no code implementations • 2 Nov 2020 • JungHoon Kim, Seyyedali Hosseinalipour, Taejoon Kim, David J. Love, Christopher G. Brinton
Applications of intelligent reflecting surfaces (IRSs) in wireless networks have attracted significant attention recently.
no code implementations • 27 Jul 2020 • Qiyou Duan, Taejoon Kim, Hadi Ghauch
We present an enhancement to the problem of beam alignment in millimeter wave (mmWave) multiple-input multiple-output (MIMO) systems, based on a modification of the machine learning-based criterion, called Kolmogorov model (KM), previously applied to the beam alignment problem.
no code implementations • 25 Jul 2020 • JungHoon Kim, Taejoon Kim, Morteza Hashemi, Christopher G. Brinton, David J. Love
Device-to-device (D2D) communications is expected to be a critical enabler of distributed computing in edge networks at scale.
no code implementations • 27 Feb 2020 • JungHoon Kim, Taejoon Kim, Morteza Hashemi, Christopher G. Brinton, David J. Love
In this paper, unlike previous mobile edge computing (MEC) approaches, we propose a joint optimization of wireless MIMO signal design and network resource allocation to maximize energy efficiency.
Networking and Internet Architecture Signal Processing