Demo Data from EDBT 2026 / reviewers in the wild / expert
Jongha Yoon
dblp:144/8312
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 2 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer networks
1 paper |
Wireless networking · 91% Internet of things and sensor networks · 9% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Wireless networking
cognitive radio |
0.3 | 1 | 2018 | Centralized Cooperative Directional Spectrum Sensing for Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2018 |
Wireless networking › cognitive radio › spectrum sensing
cooperative sensing |
0.3 | 1 | 2018 | Centralized Cooperative Directional Spectrum Sensing for Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2018 |
Wireless networking › cognitive radio
spectrum sensing |
0.3 | 1 | 2018 | Centralized Cooperative Directional Spectrum Sensing for Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2018 |
Internet of things and sensor networks › wireless sensor network › sensor fusion
fusion center |
0.1 | 1 | 2018 | Centralized Cooperative Directional Spectrum Sensing for Cognitive Radio Networks · IEEE Trans. Mob. Comput. 2018 |
Methods — techniques the papers use, named apart from their topics
nonlinear optimization · 0.3gradient descent · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Directional-antenna-based spatial and energy-efficient semi-distributed spectrum sensing in cognitive internet-of-things networks
Chunghyun Lee, Junsuk Oh, Woongsoo Na, Jongha Yoon, Wonjong Noh, Sungrae Cho |
J. Netw. Comput. Appl. | 4 |
| 2018 | Centralized Cooperative Directional Spectrum Sensing for Cognitive Radio NetworksabstractMost previous spectrum sensing techniques use omni-directional antennas. Unlike omni-directional antennas, the use of directional antennas for spectrum sensing is a promising technique that can realize fine-grained sensing for the primary user (PU) with a longer sensing range. In this paper, we propose a centralized cooperative directional sensing technique for cognitive radio networks. We assume that one secondary coordinator called the fusion center (FC), gathers sensing results from secondary nodes. Using the reported information, the FC optimizes the sensing period, sensing power, and sensing beams per secondary node. For optimization, we use a modified gradient descent method with numerical methods to solve the nonlinear optimization problem. The simulation results show that our directional spectrum sensing technique is well suited for the existing cognitive radio environment. The optimal scheme shows proposed here better performance in all simulation factors than the non-optimized scheme. Woongsoo Na, Jongha Yoon, Sungrae Cho, David W. Griffith, Nada Golmie |
IEEE Trans. Mob. Comput. | 2 |