• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.79-85
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• 2019

We investigate the D2D utility maximization in the cellular system. We focus on the non cooperative game theoretic approach to maximize the individual utility. Cellular system's perspective, interference from the D2D links must be limited to protect the cellular users. To accommodate this interference issue, utility function is first defined to control the individual D2D user's transmit power. More specifically, utility function includes the pricing which limits the individual D2D user's transmit power. Then, non cooperative power game is formulated to maximize the individual utility. Distributed algorithm is proposed to maximize the individual utility, while limiting the interference. Convergence of the proposed distributed algorithm is verified through computer simulation. Also the effect of pricing factor to SIR and interference is provided to show the performance of the proposed distributed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4680-4697
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• 2017

In future, since the user experience plays a more and more important role in the development of today's communication systems, quality of experience (QoE) becomes a widely used metric, which reflects the subjective experience of end users for wireless service. In addition, the energy efficiency is an increasingly important problem with the explosive growth in the amount of wireless terminals and nodes. Hence, a QoE-aware energy efficiency maximization based joint user access selection and power allocation approach is proposed to solve the problem. We transform the joint allocation process to an optimization of energy efficiency by establishing an energy efficiency model, and then the optimization problem is solved by chaotic clone immune algorithm (CCIA). Numerical simulation results indicate that the proposed algorithm can efficiently and reliably improve the QoE and ensure high energy efficiency of networks.

• Journal of Electrical Engineering and Technology
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• v.13 no.2
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• pp.800-811
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• 2018

This paper presents a regenerative braking control scheme for Switched Reluctance Machine (SRM) drive in Electric Vehicles (EVs). The main purpose is to maximize the recovered energy during battery charging by taking into account the nonlinear physical characteristics of the Switched Reluctance Machine. The proposed regenerative braking method employs the back-EMF in the generation process as a complicated position-dependent voltage source. The proposed maximum power recovery (MPR) operation of the regenerative braking is first based on the maximization of the extracted power from the machine and then the maximization of the power transferred to the battery. The maximum power extraction (MPE) from SRM is based on maximizing the energy conversion ratio by the calculation of the optimum PWM switching duty cycle, turn-on, and turn-off angles. By using the impedance matching theorem that allows the maximum power transfer (MPT) of the MPE, the proposed MPR is achieved. The parametric averaged value modeling of the machine phase currents in the chopping control mode is used for MPR realization. By following this model, a nonlinear equivalent input resistance is derived for the battery internal resistance matching. The effectiveness of the proposed regenerative braking method is demonstrated through simulation results and experimental implementation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3887-3907
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• 2015

This paper introduces a full duplex single secondary user multiple-input multiple-output (FD-SSU-MIMO) cognitive radio network, where secondary user (SU) opportunistically accesses the authorized spectrum unoccupied by primary user (PU) and transmits data based on FD-MIMO mode. Then we study the network achievable average sum-rate maximization problem under sum transmit power budget constraint at SU communication nodes. In order to solve the trade-off problem between SU's sensing time and data transmission time based on opportunistic spectrum access (OSA) and the power allocation problem based on FD-MIMO transmit mode, we propose a simple trisection algorithm to obtain the optimal sensing time and apply an alternating optimization (AO) algorithm to tackle the FD-MIMO based network achievable sum-rate maximization problem. Simulation results show that our proposed sensing time optimization and AO-based optimal power allocation strategies obtain a higher achievable average sum-rate than sequential convex approximations for matrix-variable programming (SCAMP)-based power allocation for the FD transmission mode, as well as equal power allocation for the half duplex (HD) transmission mode.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.11a
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• pp.481-482
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• 2008

This investigation presents a method to design an optimal shape of a matching waveguide connecting two waveguides having different impedances. The design objective is to maximize power transmission through the waveguide system. When an incident wave impinges on an elastic waveguide system consisting of waveguides of different impedances, all of the incident wave power may not pass through due to the mechanical impedance. Therefore, the maximization of the transmitted power through a waveguide difficult to achieve without a systematic design method. In this work, the optimal shape design of a matching waveguide connecting two waveguides of different impedances is formulated as a shape optimization problem. If the material of the matching waveguide is given, its shape is the only parameter controlling the transmission power. Relatively simple one dimensional elastic wave transmission problems will be considered in this work, but the underlying methodology and the related physics can be clearly demonstrated. The influences of initial configurations as well as the target frequencies on the optimized shapes will be also investigated.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.583-585
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• 2016

The recent advances in wireless networks area have led to new techniques, such as small cells or full-duplex (FD) transmission, have also been developed to further increase the network capacity. Particularly, full-duplex communication promises expected throughput gain by doubling the spectrum compared to half-duplex (HD) communication. Because this technique permits one set of frequencies to simultaneously transmit and receive signals. In this paper, we focus on the binary power control for the users and the base stations in full-duplex multiple cellulars wireless networks to obtain optimal sum-rate under the effect interference and noise. We investigate with a scenario in there one carrier is assigned to only one user in each cell and construct a model for this problem. In this work, we apply the binary power control by the its simplification in the implemented algorithm for both uplink and downlink simultaneously to maximize sum data rate of the system. At first, we realize the 2-cells case separately to check the optimal power allocation whether being binary. Then, we carry on with N-cells case in general through properties of binary power control.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.23 no.8
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• pp.556-561
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• 2011

In this study, the theoretical maximum power of a heat engine was investigated by sequential Carnot cycle model, for a low-grade heat source of about $100^{\circ}C$. In contrast to conventional approaches, the pattern search algorithm was employed to optimize the two design variables to maximize power. Variations of the maximum power and the optimum values of design variables were investigated for a wide range of UA(overall heat transfer conductance) change. The results show that maximizing heat source utilization does not always maximize power.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.334-345
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• 2010

In this paper, we study optimal tradeoffs of achievable throughput versus consumed power in wireless ad-hoc networks formed by a collection of multiple antenna nodes. Relying on adaptive modulation and/or dynamic channel coding rate allocation techniques for multiple antenna systems, we examine the maximization of throughput under power constraints as well as the minimization of transmission power under throughput constraints. In our examination, we also consider the impacts of enforcing quality of service requirements expressed in the form of channel coding block loss constraints. In order to properly model temporally correlated loss observed in fading wireless channels, we propose the use of finite-state Markov chains. Details of fading statistics of signal-to-interference-noise ratio, an important indicator of transmission quality, are presented. Further, we objectively inspect complexity versus accuracy tradeoff of solving our proposed optimization problems at a global as oppose to a local topology level. Our numerical simulations profile and compare the performance of a variety of scenarios for a number of sample network topologies.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.36-44
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• 2010

When multi-user MIMO (Multiple-Input Multiple-Output) systems utilize a sum-rate maximization (SRM) scheduler, the throughput of the systems can be enhanced. However, fairness problems may arise because users located near cell edge or experiencing poor channel conditions are less likely to be selected by the SRM scheduler. In this paper, a weighted sum-rate maximization (WSRM) scheduler is used to enhance the fairness performance of the MIMO systems. Closed-form expressions for the optimal transmit power allocation of WSRM and corresponding weighted sum-rate (WSR) are derived in the 6-sector collaborative transmission system. Using the derived results, we propose an algorithm which searches the optimal power allocation for WSRM in the 3-sector collaborative transmission system. Based on the derived closed-form expressions and the proposed algorithm, we perform computer simulations to compare performance of the WSRM scheduler and the SRM scheduler with respect to the sum-rate and the log-sum-of-average rates. We further verify that the WSRM scheduler efficiently improves fairness performance by showing the enhanced performance of average transmission rates in low percentile region.

• ETRI Journal
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• v.42 no.6
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• pp.846-858
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• 2020

The non-orthogonal multiple access (NOMA) technique offers throughput improvement to meet the demands of the future generation of wireless communication networks. The objective of this work is to further improve the throughput by including an underlay cognitive radio network with an existing multi-carrier NOMA network, using cooperative communication. The throughput is maximized by optimal resource allocation, namely, power allocation, subcarrier assignment, relay selection, user pairing, and subcarrier pairing. Optimal power allocation to the primary and secondary users is accomplished in a way that target rate constraints of the primary users are not affected. The throughput maximization is a combinatorial optimization problem, and the computational complexity increases as the number of users and/or subcarriers in the network increases. To this end, to reduce the computational complexity, a dynamic network resource allocation algorithm is proposed for combinatorial optimization. The simulation results show that the proposed network improves the throughput.