Jun Heo

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

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

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

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

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.

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

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

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

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

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

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

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

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

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

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