• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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• pp.202-215
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• 2023

This paper proposes a non-orthogonal multiple access (NOMA) based low-complexity relaying approach for multiuser cellular two-way relay channels (CTWRCs). In the proposed scheme, the relay detects the signal using successive interference cancellation (SIC) and re-generates the transmit signal with zero-forcing (ZF) transmit precoding. The achievable data rates of the NOMA-based multiuser two-way relaying (TWR) approach is analyzed. We further study the power allocation among different data streams to maximize the weighted sum-rate (WSR). We re-form the resultant non-convex problem into a standard monotonic program. Then, we design a polyblock outer approximation algorithm to sovle the WSR problem.The proposed optimal power allocation algorithm converges fast and it is shown that the NOMA-TWR-OPA scheme outperforms a NOMA benchmark scheme and conventional TWR schemes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.149-168
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• 2015

In cognitive radio networks (CRNs), hybrid overlay and underlay sharing transmission mode is an effective technique for improving the efficiency of radio spectrum. Unlike existing works in the literature, where only one secondary user (SU) uses overlay and underlay modes, the different transmission modes should be allocated to different SUs, according to their different quality of services (QoS), to achieve the maximal efficiency of radio spectrum. However, hybrid sharing mode allocation for heterogeneous services is still a challenge in CRNs. In this paper, we propose a new resource allocation method for hybrid sharing transmission mode of overlay and underlay (HySOU), to achieve more potential resources for SUs to access the spectrum without interfering with the primary users. We formulate the HySOU resource allocation as a mixed-integer programming problem to optimize the total system throughput, satisfying heterogeneous QoS. To decrease the algorithm complexity, we divide the problem into two sub-problems: subchannel allocation and power allocation. Cutset is used to achieve the optimal subchannel allocation, and the optimal power allocation is obtained by Lagrangian dual function decomposition and subgradient algorithm. Simulation results show that the proposed algorithm further improves spectrum utilization with a simultaneous fairness guarantee, and the achieved HySOU diversity gain is a satisfactory improvement.

• Journal of Korea Water Resources Association
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• v.52 no.10
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• pp.707-718
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• 2019

The optimal water allocation pursues a reliable and economic supply of water resources to meet various interests in socio-economic-environmental aspects. The global water shortage has intensified due to climate change and population growth with limited water resources. Thus, the water management scheme has shifted to improve water use efficiency by proper demand management and water allocation planning. Here, a hydro-economic water allocation model, called WAMM (Water Allocation and Management Model) is introduced. The WAMM is equipped with an improved linear programming algorithm for optimal water allocation and estimates economic value of water supply as an objective of water

• Journal of Wetlands Research
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• v.10 no.2
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• pp.155-164
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• 2008

As popultations expand and economies develop, increasing competition for limited available water resources is occurring among many water users. This has brought greater attention to water allocation with legal and institutional constraints. This paper develops a optimal water allocation methodology to basinwide water resources allocation, which ensures that scare water resources are allocated among competing water users. The methodology need to be based on optimization technique to allocate water resources due to an extended scaled of river basin. The recommended model is developed to accomplish economic efficiency, equity and sustainability objectives. The appropriate case study is tested with various existing water right system allocation model and the recommended model. The result shows the applicability of model to the complex hydrologic system with legal and institutional constraints.

• Journal of Korean Institute of Industrial Engineers
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• v.35 no.3
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• pp.185-193
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• 2009

We consider a two-fare, two-period airline seat capacity allocation problem where consumers may choose different options in purchasing an airline ticket. A consumer may decide to wait for reopening of the same fare class ticket which is originally intended to buy, or may buy a different fare class ticket within the same period, if the originally requested fare is unavailable. We investigate the impact of the consumer buying behavior on the optimal solutions and the expected revenue.

• Journal of information and communication convergence engineering
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• v.6 no.1
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• pp.24-28
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• 2008

In RFID System, when multiple tags respond simultaneously, a collision can occur. A method that solves this collision is referred to anti-collision algorithm. Among the existing anti-collision algorithms, static framed slot allocation algorithm is very simple. But when the number of tags is variable, its performance degrades because of the fixed frame size. This paper proposes an optimal frame size allocation scheme that determines the frame size. The proposed scheme is based on the number of collision slots at every frame. According to the simulation results, the tag identification time is faster that of SFSA.

• Proceedings of the KIEE Conference
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• 1989.11a
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• pp.191-193
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• 1989

This paper presents a optimal Var allocation algorithm for minimizing power loss and improving voltage profile in a given system. In this paper, nodal input data is considered as Gaussian distribution with their mean value and their variance. A stochastic Linear Programming technique based on chance constrained method is applied to solve the probabilistic constraint. The test result in IEEE-14 Bus model system showes that the voltage distribution of load buses is improved and the power loss is more reduced than before Var allocation.

• Journal of the military operations research society of Korea
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• v.26 no.1
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• pp.34-46
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• 2000

The object of this study is to construct a model for an optimal allocation of short surface to air missile defending our targets most efficiently from hostile aircraft´s attack. For the purpose of this, we analyze and establish facility allocation concept of existing models, apply set covering theory appropriate to problem´s properties, present the process of calculating the probability of target being protected, apply Sherali-Kim´s branching variable selection strategy, and then construct the model. As constructed model apply the reducing problem with application, we confirm that we can apply the large scale, real problem.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4738-4758
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• 2017

Resource allocation plays a crucial role in multiuser multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) systems to improve overall system performance. While previously proposed resource allocation algorithms are mainly designed from the point of view of the information-theoretic, we formulate the resource allocation problem as an average bit error rate (BER) minimization problem subject to a total power constraint when considering employing realistic MIMO detection techniques. Subsequently, we derive the optimal subcarrier and power allocation algorithms for three types of well-known MIMO detectors, including the maximum likelihood (ML) detector, linear detectors, and successive interference cancellation (SIC) detectors. To reduce the complexity, we also propose a two-step suboptimal algorithm that separates subcarrier and power allocation for each detector. We also analyze the diversity gain of the proposed suboptimal algorithms for various MIMO detectors. Simulation results confirm that the proposed suboptimal algorithm for each detector can achieve a comparable performance with the optimal allocation with a much lower complexity. Moreover, it is shown that the suboptimal algorithms perform better than the conventional algorithms that are known in the literature.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.5
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• pp.1286-1302
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• 2012

In this paper, the resource allocation problem with proportional fairness rate in cognitive OFDM-based wireless network is studied. It aims to maximize the total system throughput subject to constraints that include total transmit power for secondary users, maximum tolerable interferences of primary users, bit error rate, and proportional fairness rate among secondary users. It is a nonlinear optimization problem, for which obtaining the optimal solution is known to be NP-hard. An efficient bio-inspired suboptimal algorithm called immune clonal optimization is proposed to solve the resource allocation problem in two steps. That is, subcarriers are firstly allocated to secondary users assuming equal power assignment and then the power allocation is performed with an improved immune clonal algorithm. Suitable immune operators such as matrix encoding and adaptive mutation are designed for resource allocation problem. Simulation results show that the proposed algorithm achieves near-optimal throughput and more satisfying proportional fairness rate among secondary users with lower computational complexity.