• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1325-1344
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• 2019

Recently, to satisfy mobile users' increasing data transmission requirement, energy efficiency (EE) resource allocation in distributed antenna systems (DASs) has become a hot topic. In this paper, we aim to maximize EE in DASs subject to constraints of the minimum data rate requirement and the maximum transmission power of distributed antenna units (DAUs) with different density distributions. Virtual cell is defined as DAUs selected by the same user equipment (UE) and the size of virtual cells is dependent on the number of subcarriers and the transmission power. Specifically, the selection rule of DAUs is depended on different scenarios. We develop two scenarios based on the density of DAUs, namely, the sparse scenario and the dense scenario. In the sparse scenario, each DAU can only be selected by one UE to avoid co-channel interference. In order to make the original non-convex optimization problem tractable, we transform it into an equivalent fractional programming and solve by the following two sub-problems: optimal subcarrier allocation to find suitable DAUs; optimal power allocation for each subcarrier. Moreover, in the dense scenario, we consider UEs could access the same channel and generate co-channel interference. The optimization problem could be transformed into a convex form based on interference upper bound and fractional programming. In addition, an energy-efficient DAU selection scheme based on the large scale fading is developed to maximize EE. Finally, simulation results demonstrate the effectiveness of the proposed algorithm for both sparse and dense scenarios.

• Journal of Communications and Networks
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• 제18권3호
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• pp.420-428
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• 2016

In this paper, we investigate the scheduling and power allocation for coordinated multi-point transmission in downlink long term evolution advanced (LTE-A) systems, where orthogonal frequency division multiple-access is used. The proposed scheme jointly optimizes user selection, power allocation, and modulation and coding scheme (MCS) selection to maximize the weighted sum throughput with fairness consideration. Considering practical constraints in LTE-A systems, the MCSs for the resource blocks assigned to the same user need to be the same. Since the optimization problem is a combinatorial and non-convex one with high complexity, a low-complexity algorithm is proposed by separating the user selection and power allocation into two subproblems. To further simplify the optimization problem for power allocation, the instantaneous signal-to-interference-plus-noise ratio (SINR) and the average SINR are adopted to allocate power in a single cell and multiple coordinated cells, respectively. Simulation results show that the proposed scheme can improve the average system throughput and the cell-edge user throughput significantly compared with the existing schemes with limited feedback.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권8호
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• pp.2722-2742
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• 2014

We propose methods of linear transceiver design for two different power constraints, sum relay power constraint and per relay power constraint, which determine signal processing matrices such as base station (BS) transmitter, relay precoders and user receivers to minimize sum mean square error (SMSE) for multi-relay multi-user (MRMU) networks. However, since the formulated problem is non-convex one which is hard to be solved, we suboptimally solve the problems by defining convex subproblems with some fixed variables. We adopt iterative sequential designs of which each iteration stage corresponds to each subproblem. Karush-Kuhn-Tucker (KKT) theorem and SMSE duality are employed as specific methods to solve subproblems. The numerical results verify that the proposed methods provide comparable performance to that of a full relay cooperation bound (FRCB) method while outperforming the simple amplify-and-forward (SAF) and minimum mean square error (MMSE) relaying in terms of not only SMSE, but also the sum rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1837-1860
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• 2020

We propose a general framework for studying resource allocation problem and the tradeoff between spectral efficiency (SE) and energy efficiency (EE) for downlink traffic in power domain-non-orthogonal multiple access (PD-NOMA) and device to device (D2D) based heterogeneous cloud radio access networks (H-CRANs) under imperfect channel state information (CSI). The aim is jointly optimize radio remote head (RRH) selection, spectrum allocation and power control, which is formulated as a multi-objective optimization (MOO) problem that can be solved with weighted Tchebycheff method. We propose a low-complexity algorithm to solve user association, spectrum allocation and power coordination separately. We first compute the CSI for RRHs. Then we study allocating the cell users (CUs) and D2D groups to different subchannels by constructing a bipartite graph and Hungrarian algorithm. To solve the power control and EE-SE tradeoff problems, we decompose the target function into two subproblems. Then, we utilize successive convex program approach to lower the computational complexity. Moreover, we use Lagrangian method and KKT conditions to find the global optimum with low complexity, and get a fast convergence by subgradient method. Numerical simulation results demonstrate that by using PD-NOMA technique and H-CRAN with D2D communications, the system gets good EE-SE tradeoff performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권2호
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• pp.545-563
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• 2015

Energy harvesting (EH) and network coding (NC) have emerged as two promising technologies for future wireless networks. In this paper, we combine them together in a single system and then present a time switching-based network coding relaying (TSNCR) protocol for the two-way relay system, where an energy constrained relay harvests energy from the transmitted radio frequency (RF) signals from two sources, and then helps the two-way relay information exchange between the two sources with the consumption of the harvested energy. To evaluate the system performance, we derive an explicit expression of the outage probability for the proposed TSNCR protocol. In order to explore the system performance limit, we formulate an optimization problem to minimize the system outage probability. Since the problem is non-convex and cannot be directly solved, we design a genetic algorithm (GA)-based optimization algorithm for it. Numerical results validate our theoretical analysis and show that in such an EH two-way relay system, if NC is applied, the system outage probability can be greatly decreased. Moreover, it is shown that the relay position greatly affects the system performance of TSNCR, where relatively worse outage performance is achieved when the relay is placed in the middle of the two sources. This is the first time to observe such a phenomena in EH two-way relay systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권1호
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• pp.188-210
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• 2022

As a promising technique to support tremendous numbers of Internet of Things devices and a variety of applications efficiently, mobile edge computing (MEC) has attracted extensive studies recently. In this paper, we consider a MEC-assisted peer-to-peer (P2P) mobile communication system where MEC servers are deployed at access points to accelerate the communication process between mobile terminals. To capture the tradeoff between the time delay and the energy consumption of the system, a cost function is introduced to facilitate the optimization of the computation and communication resources. The formulated optimization problem is non-convex and is tackled by an iterative block coordinate descent algorithm that decouples the original optimization problem into two subproblems and alternately optimizes the computation and communication resources. Moreover, the MEC-assisted P2P communication system is compared with the conventional P2P communication system, then a condition is provided in closed-form expression when the MEC-assisted P2P communication system performs better. Simulation results show that the advantage of this system is enhanced when the computing capability of the receiver increases whereas it is reduced when the computing capability of the transmitter increases. In addition, the performance of this system is significantly improved when the signal-to-noise ratio of hop-1 exceeds that of hop-2.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권11호
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• pp.5209-5228
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• 2016

Device-to-device (D2D) communication underlaying cellular networks can bring significate benefits for improving the performance of mobile services. However, it hinges on elaborate resource sharing scheme to coordinate interference between cellular users and D2D pairs. We formulate a joint mode selection, link allocation and power control optimization problem for D2D communication sharing uplink resources in a multi-user cellular network and consider the efficiency and the fairness simultaneously. Due to the non-convex difficulty, we propose a three-step scheme: firstly, we conduct mode selection for D2D pairs based on a minimum distance metric after an admission control and obtain some cellular candidates for them. And then, a cellular candidate will be paired to each D2D pair based on fairness. Finally, we use Lagrangian Algorithm to formulate a joint power control strategy for D2D pairs and their reused cellular users and a closed-form of solution is derived. Simulation results demonstrate that our proposed algorithms converge in a short time. Moreover, both the sum rate of D2D pairs and the energy efficiency of cellular users are improved.

• Structural Engineering and Mechanics
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• 제29권5호
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• pp.489-504
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• 2008

In piezoelectric flexible structures, the contribution of vibration modes to the dynamic response of system may change with the location of piezoelectric actuator patches, which means that the ability of actuators to control vibration modes should be taken into account in the development of modal reduction model. The spatial $H_2$ norm of modes, which serves as a measure of the intensity of modes to system dynamical response, is used to pick up the modes included in the reduction model. Based on the reduction model, the paper develops the state-space representation for uncertain flexible tructures with piezoelectric material as non-collocated actuators/sensors in the modal space, taking into account uncertainties due to modal parameters variation and unmodeled residual modes. In order to suppress the vibration of the structure, a dynamic output feedback control law is designed by imultaneously considering the conflicting performance specifications, such as robust stability, transient response requirement, disturbance rejection, actuator saturation constraints. Based on linear matrix inequality, the vibration control design is converted into a linear convex optimization problem. The simulation results show how the influence of vibration modes on the dynamical response of structure varies with the location of piezoelectric actuators, why the uncertainties should be considered in the reductiom model to avoid exciting high-frequency modes in the non-collcated vibration control, and the possiblity that the conflicting performance specifications are dealt with simultaneously.

• Journal of the Korean Data and Information Science Society
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• 제28권6호
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• pp.1229-1244
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• 2017

최근 여러 분야에서 데이터에 근거한 분석방법론에 대한 수요가 증대됨에 따라 이를 처리할 수 있는 최적화 방법이 발전되고 있다. 특히 통계학과 기계학습 분야의 문제들에서 요구되는 다양한 제약 조건은 볼록 최적화 (convex optimization) 방법으로 해결할 수 있다. 본 논문에서 리뷰하는 alternating direction method of multipliers (ADMM) 알고리즘은 선형 제약 조건을 효과적으로 처리할 수 있으며, 합의 방식을 통해 병렬연산을 수행할 수 있어서 범용적인 표준 최적화 툴로 자리매김 되고 있다. ADMM은 원래의 문제보다 최적화가 쉬운 부분문제로 분할하고 이를 취합함으로써 복잡한 원 문제를 해결하는 방식의 근사알고리즘이다. 부드럽지 않거나 복합적인 (composite) 목적 함수를 최적화할 때 유용하며, 쌍대이론과 proximal 작용소 이론을 토대로 체계적으로 알고리즘을 구성할 수 있기 때문에 통계 및 기계학습 분야에서 폭 넓게 활용되고 있다. 본 논문에서는 최근 통계와 관련된 여러 분야에서 ADMM알고리즘의 활용도를 살펴보고자 하며 주요한 두 가지 주제에 중점을 두고자 한다. (1) 목적식의 분할 전략과 증강 라그랑지안 방법 및 쌍대문제의 설명과 (2) proximal 작용소의 역할이다. 알고리즘이 적용된 사례로, 별점화 함수 추정 등의 조정화 (regularization)를 활용한 방법론들을 소개한다. 모의 자료를 활용하여 lasso 문제의 최적화에 대한 실증결과를 제시한다.

• 한국수자원학회논문집
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• 제52권10호
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• pp.681-695
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• 2019

Transient Stroage Model (TSM)은 하천을 본류대와 저장대로 나누어 각각에 대한 오염물의 혼합거동을 해석함으로써 복잡한 하천에 유입된 오염물질 혼합을 이해하는 데에 가장 많이 이용되는 모형 중 하나이다. TSM의 매개변수들은 역산모형을 통해 산정하게 되는데 이는 자연하천에서 추적자실험을 통해 계측된 농도곡선에 가장 잘 맞는 TSM 모의 농도곡선을 찾는 최적화 문제이다. 저장대모형의 매개변수 산정에 관한 선행 연구들에 의해 매개변수를 산정하는 최적화 문제의 비볼록(non-convex) 특성에서 오는 불확실성이 보고되어 왔다. 본 연구에서는 청미천에서 수행된 추적자실험으로부터 취득된 농도곡선을 이용해 최상의 최적화 기법과 목적함수의 조합에 대해 분석하였다. 최적화 문제의 수렴성과 수렴 속도를 모두 만족하는 최적화 조건을 결정하기 위해 SCE-UA의 CCE와 SP-UCI의 MCCE와 같은 진화 알고리즘 기반의 전역 최적화 방법들과 오차 기반 목적함수들을 Shuffled Complex-Self Adaptive Hybrid EvoLution (SC-SAHEL)을 활용해 비교하였다. 전반적인 변수 산정 결과 여러 EA를 동시에 적용한 SC-SAHEL을 평균 제곱오차를 목적함수로 한 방법이 가장 빠르고 가장 안정적으로 최적해에 수렴하는 것으로 나타났다.