• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.79-88
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• 2003

In this paper, we study the efficiency of the stratified estimator in related with the variance lower bound of Horvitz-Thompson estimator subject to the superpopulation model. Especially, we compare the variance lower bound of optimum allocation with that of power allocation subject to Dalenius-Hedges stratification.

• Journal of the Korea Society of Computer and Information
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• v.21 no.10
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• pp.37-42
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• 2016

We investigate multi user joint rate scheduling and power allocation problem for a delay sensitive CDMA systems. First, we characterize the existing two user joint rate scheduling and power allocation. We then extend the problem to the case of the multi user systems. In general, there is no simple optimum solution for the multi user scheduling problem. To that end, we propose a sub optimum solution, termed 'virtual user approach'. We show the performance of the virtual user approach to verify the benefit of complexity.

• Advances in Energy Research
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• v.6 no.1
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• pp.55-73
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• 2019

The cost incurred by voltage sag effect in power networks has always been of important concern for discussions. Due to the environmental constraints, fossil fuel shortage crisis and low efficiency of conventional power plants, decentralized generation and renewable based DG have become trends in recent decades; because DGs can reduce the voltage sag effect in distribution networks noticeably; therefore, optimum allocation of DGs in order to maximize their effectiveness is highly important in order to maximize their effectiveness. In this paper, a new method is proposed for calculating the cost incurred by voltage sag effect in power networks. Thus, a new objective function is provided that comprehends technical standards as minimization of the cost incurred by voltage sag effect, active power losses and economic criterion as the installation and maintenance costs of DGs. Considering operational constraints of the system, the optimum allocation of DGs is a constrained optimization problem in which Lightning Attachment procedure optimization (LAPO) is used to resolve it and is the optimum number, size and location of DGs are determined in IEEE 33 bus test system and IEEE 34 bus test system. The results show that optimum allocation of DGs not only reduces the cost incurred by voltage sag effect, but also improves the other characteristics of the system.

• Journal of Electrical Engineering and Technology
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• v.4 no.3
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• pp.337-345
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• 2009

Deregulation in power industry has made the reactive power ancillary service management a critical task to power system operators from both technical and economic perspectives. Reactive power management in power systems is a complex combinatorial optimization problem involving nonlinear functions with multiple local minima and nonlinear constraints. This paper proposes a practical market-based reactive power ancillary service management scheme to tackle the challenge. In this paper a new model for voltage security and reactive power management is presented. The proposed model minimizes reactive support cost as an economic aspect and insures the voltage security as a technical constraint. For modeling validation study, two optimization algorithm, a genetic algorithm (GA) and particle swarm optimization (PSO) method are used to solve the problem of optimum allocation of reactive power in power systems under open market environment and the results are compared. As a case study, the IEEE-30 bus power system is used. Results show that the algorithm is well competent for optimal allocation of reactive power under practical constraints and price based conditions.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.49 no.6
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• pp.98-104
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• 2012

We consider the optimum power allocation problem for downlink system throughput maximization in a 2 time slotted relay interference channel. Base station (BS) transmits power to Mobile Station (MS) and Relay Station (RS) in time slot 1 (orthogonal channel). In time slot 2, BS and RS transmit power to each MS, while causing cochannel interference to each other. The obtained optimum power allocation scheme allows simultaneous transmissions of BS and RS when the interference level in time slot 2 is low. However, when the interference level is high, RS shuts down its power. Numerical results are provided to support our analysis.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2081-2101
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• 2016

Successive interference cancellation (SIC) is considered to be a promising technique to mitigate multi-user interference and achieve concurrent uplink transmissions, but the optimal power allocation (PA) issue for SIC users is not well addressed. In this article, we focus on the optimization of the PA ratio of users on an SIC channel and analytically obtain the optimal PA ratio with regard to the signal-to-interference-plus-noise ratio (SINR) threshold for successful demodulation and the sustainable demodulation error rate. Then, we design an efficient resource allocation (RA) scheme using the obtained optimal PA ratio. Finally, we compare the proposal with the near-optimum RA obtained by a simulated annealing search and the RA scheme with random PA. Simulation results show that our proposal achieves a performance close to the near-optimum and much higher performance than the random scheme in terms of total utility and Jain's fairness index. To demonstrate the applicability of our proposal, we also simulate the proposal in various network paradigms, including wireless local area network, body area network, and vehicular ad hoc network.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.25-33
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• 2017

NOMA (Non-orthogonal multiple access) system becoming a strong candidate for 5G cellular system of its high spectral efficiency. This paper considers an optimal power allocation scheme to minimize the outage probability of a user relay based cooperative NOMA system. We first derive the outage probabilities of the relay user (RU) and the destination user (DU) with selection combining. Based on these probabilities, the outage probability of the cooperative NOMA system is obtained. The analytical results are verified by Monte Carlo simulation. It is noticed that the outage probability of cooperative NOMA system has a convex function, the optimum power allocation coefficient, which satisfied the minimum outage probability, is calculated. Numerical examples show that the optimal power allocation coefficient increases with the required capacity of DU. While the capacity of DU is fixed, we noticed that the increase of the required capacity of RU decreases the optimal power allocation coefficient.

• Journal of the Korean Institute of Navigation
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• v.5 no.1
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• pp.1-23
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• 1981

As far as transportation problems are concerned, the minimization of transportation cost is the most prevailing object. But in some cases, the cargo delivery time is the utter problem rather than the cost. For instance, we may imagine the case that the delivery of the construction materials is delayed behind the schedule and this makes the construction cost increased because of idle time of other materials and man power, in addition to the indemnity. Therefore the allocation of ships, in marine transportation which is now the main route of overseas trade, to the needed area on the required time is to be appropriately performed. However, there are several restrictions for cargo delivery to meet the demand, such as ship's size, number to be employed and cargo handling capacity of the ports, etc. And there are some other factors to be considered, that is, the degree of necessities of commodities, on their kinds, amount, and the time of arrival, etc. This paper deals with the problem of optimum allocation of ships emphasizing the cargo delivery time adopting Linear Programming technique with those cargo delivery restrictions and factors transformed by introducing the multi-speed conception, the conversion of multi-commodity to a single commodity, allowable delivery time, weight penalty number and nominating priority. This paper presents a case of optimum allocation of ships in the light of cargo delivery time for a construction company which has two different construction places and analyzes the result. This study will give a planner a good tool for optimum planning of maring transportation and be used for decision of schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.4
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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.

• ETRI Journal
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• v.44 no.6
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• pp.955-965
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• 2022

A low Earth orbit (LEO) satellite constellation could be used to provide network coverage for the entire globe. This study considers multi-beam frequency reuse in LEO satellite systems. In such a system, the channel is time-varying due to the fast movement of the satellite. This study proposes an efficient power and bandwidth allocation method that employs two linear machine learning algorithms and take channel conditions and traffic demand (TD) as input. With the aid of a simple linear system, the proposed scheme allows for the optimum allocation of resources under dynamic channel and TD conditions. Additionally, efficient projection schemes are added to the proposed method so that the provided capacity is best approximated to TD when TD exceeds the maximum allowable system capacity. The simulation results show that the proposed method outperforms existing methods.