• ETRI Journal
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• 제34권6호
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• pp.879-884
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• 2012

When the number of users is finite, the performance improvement of the orthogonal random beamforming (ORBF) scheme is limited in high signal-to-noise ratio regions. In this paper, to improve the performance of the ORBF scheme, the user set and transmit power allocation are jointly determined to maximize sum rate under the total transmit power constraint. First, the transmit power allocation problem is expressed as a function of a given user set. Based on this expression, the optimal user set with the maximum sum rate is determined. The suboptimal procedure is also presented to reduce the computational complexity, which separates the user set selection procedure and transmit power allocation procedure.

• 디지털산업정보학회논문지
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• 제14권3호
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• pp.77-85
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• 2018

Multi-User Multiple-Input Multiple-Output (MU-MIMO) is the core technology for improving the channel capacity compared to Single-User MIMO (SU-MIMO) by using multiuser gain and spatial diversity. Key problem for the MU-MIMO is the user selection which is the grouping the users optimally. To solve this problem, we adopt Extreme Value Theory (EVT) at the beginning of the proposed algorithm, which defines a primary user set instead of a single user that has maximum channel power according to a predetermined threshold. Each user in the primary set is then paired with all of the users in the system to define user groups. By comparing these user groups, the group that produces a maximum sum rate can be determined. Through computer simulations, we have found that the proposed method outperforms the conventional technique yielding a sum rate that is 0.81 bps/Hz higher when the transmit signal to noise ratio (SNR) is 30 dB and the total number of users is 100.

• 한국통신학회논문지
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• 제34권6A호
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• pp.494-499
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• 2009

본 논문에서는 하향링크 다중 사용자 Multiple Input Multiple Output (MIMO) 채널 환경에서 시스템 용량을 최대화시키기 위한 효과적인 사용자 선택 기법에 대해서 논의한다. 본 논문에서 제안하는 방법은 사용자 채널 파워와 채널 간의 각도를 이용하여 최적의 사용자 집단을 선택하는 새로운 방법이다. 이 방법은 SUS 방법에 비해 허용 상관도 값을 별도로 생각하지 않아도 되기 때문에 간단한 방법이며, 시스템 성능을 최대화시키는 사용자들을 찾는 방법이기 때문에 향상된 성능을 보인다.

• ETRI Journal
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• 제41권5호
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• pp.626-636
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• 2019

A novel algorithm for joint user selection and optimal power allocation for Stackelberg game-based revenue maximization in a downlink non-orthogonal multiple access (NOMA) network is proposed in this study. The condition for the existence of optimal solution is derived by assuming perfect channel state information (CSI) at the transmitter. The Lagrange multiplier method is used to convert the revenue maximization problem into a set of quadratic equations that are reduced to a regular chain of expressions. The optimal solution is obtained via a univariate iterative procedure. A simple algorithm for joint optimal user selection and power calculation is presented and exhibits extremely low complexity. Furthermore, an outage analysis is presented to evaluate the performance degradation when perfect CSI is not available. The simulation results indicate that at 5-dB signal-to-noise ratio (SNR), revenue of the base station improves by at least 15.2% for the proposed algorithm when compared to suboptimal schemes. Other performance metrics of NOMA, such as individual user-rates, fairness index, and outage probability, approach near-optimal values at moderate to high SNRs.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2001년도 정기총회 및 학술대회
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• pp.189-192
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• 2001

In this paper, we propose a method of loaming user preference for set-top box scenario. Our proposed method analyzes user history data to learn user preference and then automatically suggest the list of TV programs to the user under the assumption that the TV programs are regularly repeated on time and daily basis. We used MPEG-7 MDS to describe user history data. The experiment results show the proposed method yielded a good performance.

• 제어로봇시스템학회논문지
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• 제12권7호
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• pp.666-670
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• 2006

This paper presents the novel feature selection method for Emotion Recognition, which may include a lot of original features. Specially, the emotion recognition in this paper treated speech signal with emotion. The feature selection has some benefits on the pattern recognition performance and 'the curse of dimension'. Thus, We implemented a simulator called 'IFS' and those result was applied to a emotion recognition system(ERS), which was also implemented for this research. Our novel feature selection method was basically affected by Reinforcement Learning and since it needs responses from human user, it is called 'Interactive feature Selection'. From performing the IFS, we could get 3 best features and applied to ERS. Comparing those results with randomly selected feature set, The 3 best features were better than the randomly selected feature set.

• 한국통신학회논문지
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• 제33권9B호
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• pp.745-750
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• 2008

무선인지 기반의 시스템에서, 주 사용자를 위한 주파수 할당을 보장하면서도 부가 사용자에게도 끊김없는 서비스를 제공해야 한다. 부가 사용자의 멀티미디어 데이터의 전송 시 무선 링크의 빈번한 변경 때문으로 인한 데이터 전송 지연과 손실이 발생할 경우 QoS 저하를 피할 수 없게 된다. 부가 사용자에게도 끊김없는 서비스를 유지하기 위해서는 효율적인 주파수 자원 관리가 필요하다. 본 논문에서는 퍼지 다기준 의사 결정 방법에 근거한 주파수 선정 방법을 제안한다. 제안되는 주파수선정 방법은 퍼지 집합 이론을 활용하며 주파수 선택을 위한 결정 프로세스에 기존의 전파 수신 감도 이외에 셀 부하, 데이터 전송률, 가용 대역 등을 고려한다. 시뮬레이션을 통하여, 제안된 방법이 수신 신호 세기만을 사용하는 기존의 방법보다 우수함을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권7호
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• pp.2972-2991
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• 2016

WLAN is the best choice in the place where complex network is hard to set up. Intelligent terminals are more and more assembled in some areas now. However, according to IEEE 802.11n/802.11ac, the access-point (AP) can only serve one user at a single frequency channel. The spectrum efficiency urgently needs to be improved. In theory, AP with multi-antenna can serve multiple users if these users do not interfere with each other. In this paper, we propose a user clustering scheme that could achieve multi-user selection through the mutual cooperation among users. We focus on two points, one is to achieve multi-user communication with multiple antennas technique at a single frequency channel, and the other one is to use a way of distributed users' collaboration to determine the multi-user selection for user clustering. Firstly, we use the CSMA/CA protocol to select the first user, and then we set this user as a source node using users' cooperation to search other proper users. With the help of the users' broadcast cooperation, we can search and select other appropriate user (while the number of access users is limited by the number of antennas in AP) to access AP with the first user simultaneously. In the network node searching, we propose a maximum degree energy routing searching algorithm, which uses the shortest time and traverses as many users as possible. We carried out the necessary analysis and simulation to prove the feasibility of the scheme. We hope this work may provide a new idea for the solution of the multiple access problem.

• International Journal of Contents
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• 제3권4호
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• pp.15-21
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• 2007

Image morphing deals with the metamorphosis of one image into another. The field morphing depends on the manual work for most of the process, where a user has to designate the control lines. It takes time and requires skills to have fine quality results. It is an object of this paper to propose a method capable of realizing the semi-automation of field morphing using adaptive vertex correspondence based on image segmentation. The adaptive vertex correspondence process efficiently generates a pair of control lines by adaptively selecting reference partial contours based on the number of vertices that are included in the partial contour of the source morphing object and in the partial contour of the destination morphing object, in the pair of the partial contour designated by external control points through user input. The proposed method generates visually fluid morphs and warps with an easy-to-use interface. According to the proposed method, a user can shorten the time to set control lines and even an unskilled user can obtain natural morphing results as he or she designates a small number of external control points.

• 한국지능시스템학회논문지
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• 제16권6호
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• pp.647-652
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• 2006

본 논문은 일반적으로 많은 특징들을 갖고 있는 패턴 분류 문제인 감정 인식을 위한 새로운 특징 선택 방법을 제안한다. '특징 선택'은 패턴 인식 성능의 향상에 기여하고 '차원의 저주'문제에도 좋은 해결책으로 많이 사용되는 방법이다. 그래서, 본 논문에서는 강화학습의 개념을 사용한 상호 작용에 의한 특징 선택 방법인 IFS(Interactiv Feature Selection)를 고안하였고 이 알고리즘을 사용하여 선택된 특징들을 감정 인식 시스템에 적용하여 성능이 향상됨을 확인하였다. 또한 기존의 특징 선택 방법과의 비교를 통하여 본 알고리즘의 우수성을 확인하였다.