• 한국통신학회논문지
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• 제39B권10호
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• pp.664-673
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• 2014

본 논문은 기지국 간 상하향링크의 할당 비율이 동일하지 않은 비동기식 시분할 듀플렉싱 모드 기반의 이종 네트워크 환경에서 총 전송률을 최대화 하는 전력 할당 방식을 연구한다. 본 논문에서는 매크로 셀 커버리지 안에 같은 자원을 공유하는 소형 셀이 존재하는 이종 네트워크를 고려한다. 각 셀 마다 주어진 Target 수신 신호 대 간섭 및 잡음 비 성능을 만족하면서 각 셀의 전송률의 합을 목적 함수로 가지는 최적화 문제를 정의한다. 이를 통해 최적 해가 존재하기 위한 가시적인 영역을 분석하고 총 전송률을 최대화 할 수 있는 전력 할당 방식을 도출한다. 실험 결과를 통하여 제안한 전력 할당 방식을 사용한 전송 방식이 모든 노드가 최대 허용 전력으로 전송하는 전송 방식보다 더 높은 전송률을 달성함을 확인할 수 있다.

• 대한전기학회논문지:전력기술부문A
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• 제53권3호
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• pp.182-186
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• 2004

In this paper, the cost for capacitive reactive flower is evaluated considering the deregulation environment. For the cost assessment of reactive power, the duration curve of reactive power demand is introduced and investigated. Also, a guideline is suggested to estimate the Q-cost by using the inverse of the Q-demand duration curve. In order to obtain optimal real reactive power allocation, a new algorithm is proposed by using the piecewise linearization of the inverse of the Q-demand duration curve and the Linear Programming technique. The proposed method is tested with sample systems using MATLAB. The test results show that the algorithm yields reasonable reactive power allocation and Provides fair cost evaluation for reactive power.

• Journal of Communications and Networks
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• 제11권1호
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• pp.42-46
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• 2009

Superimposed training (SIT) design for estimating of time-varying multipath channels is investigated for mobile orthogonal frequency division multiplexing (OFDM) systems. The design of optimum SIT consists of two parts: The optimal SIT sequence is derived by minimizing the channel estimates' mean square error (MSE); the optimal power allocation between training and information data is developed by maximizing the averaged signal to interference plus noise ratio (SINR) under the condition of equal powered paths. The theoretical analysis is verified by simulations. For the metric of the averaged SINR against signal to noise ratio (SNR), the theoretical result matches the simulation result perfectly. In contrast to an interpolated frequency-multiplexing training (FMT) scheme or an SIT scheme with random pilot sequence, the SIT scheme with proposed optimal sequence achieves higher SINR. The analytical solution of the optimal power allocation is demonstrated by the simulation as well.

• 전기학회논문지
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• 제60권3호
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• pp.517-523
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• 2011

A lot of DSM (Demand Side Management) programs have been implemented to promote the effective utilization of resources and the rational development of power industry, and various economic analyses and policy-based studies on DSM have been executed to determine effective subsidy budget. In this paper, a new objective function for deciding an optimal incentive allocation among various programs is presented by introducing the maximization of the total saving power of the programs. For simplicity, the objective function and the constraints is linearized to apply LP(Linear Programming) method. LP program based on Simplex Method was developed by MATLAB. An optimal incentive allocation of 4 DSM programs is presented by the use of the developed MATLAB program.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.2282-2303
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• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권7호
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• pp.2350-2364
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• 2014

This paper addresses the problem of resource allocation in amplify-and-forward (AF) relayed OFDM based cognitive radio networks (CRNs). The purpose of resource allocation is to maximize the overall throughput, while satisfying the constraints on the individual power and the interference induced to the primary users (PUs). Additionally, different from the conventional resource allocation problem, the rate-guarantee constraints of the subcarriers are considered. We formulate the problem as a mixed integer programming task and adopt the dual decomposition technique to obtain an asymptotically optimal power allocation, subcarrier pairing and relay selection. Moreover, we further design a suboptimal algorithm that sacrifices little on performance but could significantly reduce computational complexity. Numerical simulation results confirm the optimality of the proposed algorithms and demonstrate the impact of the different constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권7호
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• pp.2047-2066
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• 2024

In order to improve the coverage and achieve massive spectrum access, non-orthogonal multiple access (NOMA) technology is applied in millimeter wave massive multiple-input multiple-output (mMIMO) communication network. However, the power assumption of active sensors greatly limits its wide applications. Recently, Intelligent Reconfigurable Surface (IRS) technology has received wide attention due to its ability to reduce power consumption and achieve passive transmission. In this paper, spectral efficiency maximum problem in the millimeter wave mMIMO-NOMA system with IRS is considered. The sparse RF chain antenna structure is designed at the base station based on continuous phase modulation. Furthermore, a joint optimization problem for power allocation, power splitting, analog precoding and IRS reconfigurable matrices are constructed, which aim to achieve the maximum spectral efficiency of the system under the constraints of user's quality of service, minimum energy harvesting and total transmit power. A three-stage iterative algorithm is proposed to solve the above mentioned non-convex optimization problems. We obtain the local optimal solution by fixing some optimization parameters firstly, then introduce the relaxation variables to realize the global optimal solution. Simulation results show that the spectral efficiency of the proposed scheme is superior compared to the conventional system with phase shifter modulation. It is also demonstrated that IRS can effectively assist mmWave communication and improve the system spectral efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권12호
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• pp.5943-5962
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• 2017

A resource allocation algorithm based on simultaneous wireless information and power transfer (SWIPT) to maximize the system throughput is proposed in orthogonal frequency division multiplexing (OFDM) relay networks. The algorithm formulates the problem under the peak power constraints of the source and each subcarrier (SC), and the energy causality constraint of the relay. With the given SC allocation of the source, we give and prove the optimal propositions of the formulated problem. Then, the formulated problem could be decomposed into two separate throughput maximization sub-problems by setting the total power to transfer energy. Finally, several SC allocation schemes are proposed, which are energy priority scheme, information priority scheme, balanced allocation scheme and exhaustive scheme. The simulation results reveal that the energy priority scheme can significantly reduce computational complexity and achieve approximate performance with the exhaustive scheme.

• 한국통신학회논문지
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• 제35권7A호
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• pp.646-653
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• 2010

본 논문은 OFDM(Orthogonal Frequency Division Multiplexing; 직교 주파수 분할 다중)또는 MIMO(Multiple-input Multiple-output; 다중안테나) 시스템과 같이 여러개의 부채널이 존재하는 노드들로 구성된 다중 홉 중계 네트워크에서, 부채널할당 및 전력할당의 동시 최적화를 위한 통합적 접근방법을 제시한다. 다수의 부채널이 존재하는 경우 중계기는 전력할당외에도 첫 번째 홉과 두 번째 홉간의 부채널 matching을 통해 성능을 최적화 할 수 있게 된다. 그러나 두 홉간의 부채널 matching문제는 복잡한 조합론적 문제이므로 부채널할당과 전력할당의 동시 최적화 문제는 일반적으로 그 최적해를 구하기가 아주 어려운 문제로 알려져 있다. 하지만 본 논문에서는 재배열 부등식을 이용하여 복잡한 동시최적화 문제가 많은 경우 효율적으로 풀릴 수 있음을 보이고 다양한 예제롤 통해 제안된 접근법이 아주 유용함을 보인다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권8호
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• pp.1955-1971
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• 2013

This paper studies relay selection and power allocation for amplify-and-forward (AF) based two-way relay networks (TWRN) with asymmetric traffic requirements (ATR). A joint relay selection and power allocation algorithm is proposed to decrease the outage probability of TWRN with ATR. In this algorithm, two sources exchange information with the help of the relay during two time slots. We first calculate the optimal power allocation parameters based on instantaneous channel state information (CSI), and then derive a tight lower bound of outage probability. Furthermore, we propose a simplified relay selection criterion, which can be easily calculated as harmonic mean of instantaneous channel gains, according to the outage probability expressions. Simulation results verified the theoretical analyses we presented. It is shown that the outage probability of our algorithm improves 3-4dB comparing with that of other existing algorithms, and the lower bound is tight comparing with actual value for the entire signal-to-noise ratio (SNR) region.