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허준 교수

Jun Heo

고려대학교 차세대통신학과 · 컴퓨터과학

연구실 소개

허준 교수의 연구실은 스마트 홈의 에너지 소비 예측과 최적화, 코그니티브 라디오 기반의 스펙트럼 공유 기술, 그리고 다이렉트 디바이스(D2D) 통신 환경에서의 협업 중계 기반 성능 향상에 중점을 두고 있습니다. 특히, 시스템 시뮬레이션 기반의 에너지 소비 분석, 고밀도 부호의 반복 디코딩 성능 최적화, 데이터 은닉 및 스펙트럼 감지 기술 개선 등에 대한 깊이 있는 연구를 수행하고 있습니다. 이는 실생활 통신 및 에너지 효율성 문제 해결을 위한 기초 기술 개발을 목표로 합니다.

스마트 홈 에너지 모델링코그니티브 라디오D2D 통신LDPC 부호스펙트럼 감지

연구 현황

논문 수
94
총 인용 수
522
최근 5년 논문
15
주요 분야
컴퓨터과학

연구 성과 추이

표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.

5개년 연도별 논문 게재 수
15총합
2020
2021
2022
2025
2026
5개년 연도별 피인용 수
29총합
20202021202220252026

주요 논문

15
1
논문|인용수 66·2010
Concurrent simulation platform for energy-aware smart metering systems
Seunghyun Park, Han-Joo Kim, Hichan Moon, Jun Heo, Sungroh Yoon
SJR Q1IEEE Transactions on Consumer Electronics

We propose a simulation framework that can model a house equipped with various home appliances and next-generation smart metering devices. This simulator can predict the power dissipation profiles of individual appliances as well as the cumulative energy consumption of the house in a realistic manner. We utilize SystemC, a concurrent system-modeling methodology originally developed and populated in the design automation community. According to our experiments with various consumer electronics de

Hardware and ArchitectureComputer Science
2
논문|인용수 51·2012
An Efficient Embedder for BCH Coding for Steganography
Rongyue Zhang, Vasily Sachnev, Magnus Bakke Botnan, Hyoung Joong Kim, Jun Heo
SJR Q1IEEE Transactions on Information Theory

This paper presents an improved data hiding technique based on BCH ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</i> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</i> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">t</i> ) coding. The proposed embedder hides data into a block of input data by modifying some coefficients in the block in order to null

Computer Vision and Pattern RecognitionComputer Science
3
논문|인용수 47·2011
Cooperative TV spectrum sensing in cognitive radio for Wi-Fi networks
Chongjoon You, Hong-Kyu Kwon, Jun Heo
SJR Q1IEEE Transactions on Consumer Electronics

This paper presents cooperative spectrum sensing techniques for cognitive radio (CR) systems. The spectrum sensing detects the presence of a primary user (service) on an associated spectrum. The accuracy of spectrum sensing depends on both sensing time and number of sensing nodes (i.e. secondary users) participating in the sensing process. We derive optimal number of secondary users for cooperative spectrum sensing to minimize spectrum detection error probability and optimal spectrum sensing tim

Computer Networks and CommunicationsComputer Science
4
논문|인용수 44·2012
Performance of multihop decode-and-forward relaying assisted device-to-device communication underlaying cellular networks
Dong-Hoon Lee, Sung‐il Kim, Jaeyoung Lee, Jun Heo
International Symposium on Information Theory and its Applications

We investigate a performance of cooperative relaying in the device-to-device (D2D) systems underlaying cellular networks while considering power constraints on the average received-interference at the evolved NodeB (eNB). Specifically, we consider the D2D communication assisted by relays using multihop decode-and-forward (DF) strategy in interference existing circumstances. In this paper, we obtain exact closed-form expression for the CDF and the PDF of the received Signal-to-Interference-plus-n

Computer Networks and CommunicationsComputer Science
5
논문|인용수 44·2003
Analysis of scaling soft information on low density parity check code
Jun Heo
SJR Q3Electronics Letters

Density evolution is used to analyse the scaling of soft information in the iterative decoding of low density parity check codes. Based on the min-sum algorithm and Gaussian approximation, the thresholds are evaluated with various scaling factors. The optimal scaling factor is found by density evolution and the expected scaling gain matches well with the achievable scaling gain from simulation results.

Computer Networks and CommunicationsComputer Science
6
논문|인용수 29·2005
Optimization of Scaling Soft Information in Iterative Decoding Via Density Evolution Methods
Jun Heo, K.M. Chugg
SJR Q1IEEE Transactions on Communications

Density evolution has recently been used to analyze iterative decoding and explain many characteristics of iterative decoding including convergence of performance and preferred structures for the constituent codes. The scaling of extrinsic information (messages) has been heuristically used to enhance the performance in the iterative decoding literature, particularly based on the min-sum message passing algorithm. In this paper, it is demonstrated that density evolution can be used to obtain the

Computer Networks and CommunicationsComputer Science
7
논문|인용수 16·2006
Improved Belief Propagation (BP) Decoding for LDPC Codes with a large number of short cycles
Kyuhyuk Chung, Jun Heo

In this paper, we improve performance of Low Density Parity Check (LDPC) codes by adding a large number of short cycles. Short cycles, especially cycles of length 4, degrade performance of LDPC codes if the standard BP (Belief Propagation) decoding is used. Therefore current researches have focused on removing cycles of length 4 for designing good performance LDPC codes. We found that a large number of cycles of length 4 improve performance of LDPC codes if a modified BP decoding is used. We pre

Computer Networks and CommunicationsComputer Science
8
논문|인용수 12·2008
Performance analysis of forward error correcting codes in IPTV
Sung Hoon Kim, Sun Kim, Saejoon Kim, Jun Heo
SJR Q1IEEE Transactions on Consumer Electronics

In recent years the forward error correction (FEC) schemes at the binary erasure channel have been researched for many applications including DVB-H and IPTV systems. In most cases the packet-level FEC strategies are implemented by either Reed-Solomon (RS) codes at the link layer or Raptor codes at the application layer. Recently an enhanced decoding method for RS codes was presented. The enhanced-decoding scheme is a combination of erasure and error decoding. In this paper we consider the perfor

Computer Networks and CommunicationsComputer Science
9
논문|인용수 12·2018
Low Complexity Syndrome-Based Decoding Algorithm Applied to Block Turbo Codes
Byungkyu Ahn, Sungsik Yoon, Jun Heo
SJR Q1IEEE AccessOA

This paper presents a technique for reducing the decoding complexity of block turbo code with an extended Hamming code as a component code. In conventional decoding algorithms, when an input vector has a zero syndrome, complexity can be reduced by using the hard-input soft-output (HISO) algorithm. Although sufficient error correction can be achieved using hard decision decoding (HDD) of a component code, conventional methods have used the soft-input soft-output (SISO) algorithm for input vectors

Computer Networks and CommunicationsComputer Science
10
논문|인용수 12·2015
Fountain Code Design for Broadcasting Systems With Intermediate-State Users
Young-Kil Suh, Jonghyun Baik, Nazanin Rahnavard, Jun Heo
SJR Q1IEEE Transactions on CommunicationsOA

Several studies on fountain codes have proposed degree distribution optimization schemes to maximize symbol recovery rate. However, if the number of transmitted coded symbols is limited or the channel erasure probability is high, it may be impossible that a user recovers all of the data symbols regardless of degree distribution employed by the source. In this study, we focus on a new system model where one source transmits fountain-coded symbols to multiple users who already possess some data sy

Computer Networks and CommunicationsComputer Science
11
논문|인용수 12·2020
An advanced low-complexity decoding algorithm for turbo product codes based on the syndrome
Sungsik Yoon, Byungkyu Ahn, Jun Heo
SJR Q2EURASIP Journal on Wireless Communications and NetworkingOA

Abstract This paper introduces two effective techniques to reduce the decoding complexity of turbo product codes (TPC) that use extended Hamming codes as component codes. We first propose an advanced hard-input soft-output (HISO) decoding algorithm, which is applicable if an estimated syndrome stands for double-error. In conventional soft-input soft-output (SISO) decoding algorithms, 2 p ( p : the number of least reliable bits) number of hard decision decoding (HDD) operations are performed to c

Electrical and Electronic EngineeringEngineering
12
논문|인용수 11·2008
Low complexity decoding for Raptor codes for hybrid-ARQ systems
Jun Heo, Sung Hoon Kim, Joon Kim, Jin Kim
SJR Q1IEEE Transactions on Consumer Electronics

In this paper we present a low complexity decoding algorithm for Raptor codes which is used for incremental redundancy hybrid ARQ schemes. Encoding and decoding Raptor codes are the processes of making encoding symbols from the source symbols and the recovery of the source symbols from the received encoding symbols transmitted through an erasure channel, respectively. If the received encoding symbols are insufficient to recover the source symbols, additional encoding symbols are delivered and de

Computer Networks and CommunicationsComputer Science
13
논문|인용수 9·2016
Pre-coded LDPC coding for physical layer security
Kyung‐Hoon Kwon, Taehyun Kim, Jun Heo
SJR Q2EURASIP Journal on Wireless Communications and NetworkingOA

This paper examines a simple and practical security preprocessing scheme for the Gaussian wiretap channel. A security gap based error rate is used as a measure of security over the wire-tap channel. In previous works, information puncturing and scrambling schemes based on low-density parity-check (LDPC) codes were employed to reduce the security gap. Unlike the previous works, our goal is to improve security performance by using the precode of the feed-forward (FF) structure. We demonstrate that

Computer Networks and CommunicationsComputer Science
14
논문|인용수 5·2001
Constrained iterative decoding: performance and convergence analysis
Jun Heo, K.M. Chugg

We introduce a modification to the standard iterative decoding (message passing) algorithm that yields improved performance at the cost of higher complexity. This modification is to run multiple iterative decoders, each with a different constraint on a system variable (e.g., input value, state value etc.). This constrained iterative decoding (CID) implements optimal MAP decoding for systems represented by single-cycle graphs (e.g., tail-biting convolutional codes). For more complex graphical mod

Computer Networks and CommunicationsComputer Science
15
논문|인용수 4·2008
Efficient Decoding Algorithm for Raptor Codes for Multimedia Broadcast Services
Jun Heo, Sun-Pil Kim, J. Y. Kim

This paper presents an efficient decoding algorithm for raptor codes which are widely used for multimedia broadcast services. Decoding raptor codes is the recovery of the source symbols from the received encoding symbols transmitted through an erasure channel. If the received encoding symbols are insufficient to recover the source symbols, additional encoding symbols are delivered and decoded with the previously received encoding symbols. We propose a low complexity raptor decoding algorithm whi

Computer Networks and CommunicationsComputer Science

대표 연구 분야

Computer Networks and CommunicationsArtificial IntelligenceElectrical and Electronic EngineeringHardware and ArchitectureComputer Vision and Pattern RecognitionSignal Processing

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