• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1131-1136
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• 2020

Cooperative networks enhance the performance of communication systems by combining received signals from the several relay nodes where the source node transmits signals to relay nodes. In this paper, we analyze the effect of resource allocation in cooperative networks. We assume that the cooperative networks use the conventional modulation scheme between the source and relay nodes, and adopt space-time code between the relays and destination node. Both the synchronous and differential modulations are applied for the conventional scheme and differential modulation is used for the space-time code. We consider relay location and energy allocation for resource allocation, and the performance of cooperative networks depending on the number of relay is also investigated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.3
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• pp.921-940
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• 2015

In this paper, we investigate the multi-resource allocation problem, a unique feature of which is that the multiple resources can compensate each other while achieving the desired system performance. In particular, power and time allocations are jointly optimized with the target of energy efficiency under the resource-limited constraints. Different from previous studies on the power-time tradeoff, we consider a multi-server case where the concurrent serving users are quantitatively restricted. Therefore user selection is investigated accompanying the resource allocation, making the power-time tradeoff occur not only between the users in the same server but also in different servers. The complex multivariate optimization problem can be modeled as a variant of 2-Dimension Bin Packing Problem (V2D-BPP), which is a joint non-linear and integer programming problem. Though we use state decomposition model to transform it into a convex optimization problem, the variables are still coupled. Therefore, we propose an Iterative Dual Optimization (IDO) algorithm to obtain its optimal solution. Simulations show that the joint multi-resource allocation algorithm outperforms two existing non-joint algorithms from the perspective of energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.20-39
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• 2020

This paper considers a downlink multi-carrier cooperative non-orthogonal multiple access (NOMA) transmission, where no direct link exists between the far user and the base station (BS), and the communication between them only relies on the assist of the near user. Firstly, the BS sends a superimposed signal of the far and the near user to the near user, and then the near user adopts simultaneous wireless information and power transfer (SWIPT) to split the received superimposed signal into two portions for energy harvesting and information decoding respectively. Afterwards, the near user forwards the signal of the far user by utilizing the harvested energy. A minimum data is required to ensure the quality of service (QoS) of the far user. We jointly optimize power allocation, subcarrier allocation, time allocation, the power allocation (PA) coefficient and the power splitting (PS) ratio to maximize the number of data bits received at the near user under the energy causality constraint, the minimum data constraint and the transmission power constraint. The block-coordinate descent method and the Lagrange duality method are used to obtain a suboptimal solution of this optimization problem. In the final simulation results, the superiority of the proposed NOMA scheme is confirmed compared with the benchmark NOMA schemes and the orthogonal multiple access (OMA) scheme.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.3
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• pp.506-512
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• 2016

Recently, energy harvesting technology is considered as a tool to improve the lifetime of sensor networks by mitigating the battery capacity limitation problem. However, the previous work on energy harvesting has failed to provide practical information since it has assumed an ideal channel knowledge model with perfect channel state information at transmitter (CSIT). This paper proposes an energy efficient resource allocation scheme that takes account of the channel estimation process and the corresponding estimation error. Based on the optimization tools, we provide information on efficient scheduling and power allocation as the functions of channel estimation accuracy, harvested energy, and data rate. The simulation results confirm that the proposed scheme outperforms the conventional energy harvesting networks without considering channel estimation error in terms of energy efficiency. Furthermore, with taking account of channel estimation error, the results provides a new way for allocating resources and scheduling devices.

• Journal of Korean Institute of Industrial Engineers
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• v.43 no.3
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• pp.203-212
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• 2017

Emissions Trading System (ETS) is utilized in many countries, including South Korea, as an efficient policy to abate GHG (Greenhouse Gas) emissions. Grandfathering on the basis of historic emissions is used as the way to allocate permits in South Korea. It, however, has caused an increase in the emission permits and lack of equity. To overcome these drawbacks, we propose an alternative DEA model for centralized allocation of emission abatement to evaluate the amount of emissions abatement by company based on the energy efficiency. In addition, an empirical analysis of 36 assigned companies for ETS in Korean metal industry is conducted to validate the feasibility of the proposed model. The result of the analysis shows that energy-efficient companies achieve reduced target of the emissions abatement and companies with low energy efficiency score are turned out to have contrary outcome, against the result of applying Grandfathering.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4387-4404
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• 2015

The energy-efficient design of sensing-based spectrum sharing of a multi-input and multi-output (MIMO) cognitive radio (CR) system with imperfect multiple antenna spectrum sensing is investigated in this study. Optimal resource allocation strategies, including sensing time and power allocation schemes, are studied to maximize the energy efficiency (EE) of the secondary base station under the transmit power and interference power constraints. EE problem is formulated as a nonlinear stochastic fractional programming of a nonconvex optimal problem. The EE problem is transformed into its equivalent nonlinear parametric programming and solved by one-dimension search algorithm. To reduce searching complexity, the search range was founded by demonstration. Furthermore, simulation results confirms that an optimal sensing time exists to maximize EE, and shows that EE is affected by the spectrum detection factors and corresponding constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.565-581
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• 2019

This paper investigates the wireless powered two way relay network (WPTWRN), where two single-antenna users and one single-antenna relay firstly harvest energy from signals emitted by a multi-antenna power beacon (PB) and then two users exchange information with the help of the relay by using their harvested energies. In order to improve the energy transfer efficiency, energy beamforming at the PB is deployed. For such a network, to explore the performance limit of the presented WPTWRN, an optimization problem is formulated to obtain the achievable rate region bounds by jointly optimizing the time allocation and energy beamforming design. As the optimization problem is non-convex, it is first transformed to be a convex problem by using variable substitutions and semidefinite relaxation (SDR) and then solve it efficiently. It is proved that the proposed method achieves the global optimum. Simulation results show that the achievable rate region of the presented WPTWRN architecture outperforms that of wireless powered one way relay network architecture. Results also show that the relay location has significant impact on achievable rate region of the WPTWRN.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.112-122
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• 2016

Cognitive radio (CR) is considered an attractive technology to deal with the spectrum scarcity problem. Multi-radio access technology (multi-RAT) can improve network capacity because data are transmitted by multiple RANs (radio access networks) concurrently. Thus, multi-RAT embedded in a cognitive radio network (CRN) is a promising paradigm for developing spectrum efficiency and network capacity in future wireless networks. In this study, we consider a new CRN model in which the primary user networks consist of heterogeneous primary users (PUs). Specifically, we focus on the energy-efficient resource allocation (EERA) problem for CR users with a special location coverage overlapping region in which heterogeneous PUs operate simultaneously via multi-RAT. We propose a two-tier crossover genetic algorithm-based search scheme to obtain an optimal solution in terms of the power and bandwidth. In addition, we introduce a radio environment map to manage the resource allocation and network synchronization. The simulation results show the proposed algorithm is stable and has faster convergence. Our proposal can significantly increase the energy efficiency.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.1912-1931
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• 2018

In future wireless network, user experience and energy efficiency will play more and more important roles in the communication systems compared to their roles at present. Quality of experience (QoE) and Energy Efficiency (EE) become the widely used metrics. In this paper, we study a combinatorial problem of QoE and EE and investigate a fair power allocation in heterogeneous networks. We first design a new metric, QoE-aware EE (QEE) to reflect the relationship of QoE and energy. Then, the concept of Utopia QEE is introduced, which is defined as the achievable maximum QEE in ideal conditions, for each user. Finally, we transform the power allocation process to an optimization of ratio of QEE and Utopia QEE and use invasive weed optimization (IWO) algorithm to solve the optimization problem. Numerical simulation results indicate that the proposed algorithm can get converged and efficiently improve the system energy efficiency and the QoE for each user.

• Journal of Energy Engineering
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• v.16 no.1 s.49
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• pp.15-21
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• 2007

In order to solve problems of global warming, many policies and measures has been implemented in various countries. In January 2005, the European Union Emission Trading Scheme officially started. In order to take it into action, the EU ETS stated that all members must submit the national allocation plan including the national's total allowances, allowances for installations, reserve for new entrants, etc. In the process of this decision-making, it was also stated that problems related with early action should be solved by each member state at its option. This paper is a study on necessity of compensation for early action and its limitation of its practices. With a comparative study on dealing with early action in the key nations including Germany, the Netherlands and United Kingdom, we can get insights and strategies for effective processes of dealing with early action and the direction for harmonizing data collection and allocation rules.