• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.1C
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• pp.32-36
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• 2003

Based on oriented minimum output energy (OMOE) criterion, a new blind multiuser receiving scheme of linear minimum mean square error (MMSE) detector is proposed, then an adaptive algorithm for implementing the new scheme is given by the steepest descent method, and the convergence property of the algorithm is analyzed in this paper. The numerical results demonstrate the performance of the proposed scheme.

• Journal of Communications and Networks
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• v.8 no.3
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• pp.290-296
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• 2006

In this paper, a generalized blind adaptive algorithm is introduced for multi-user detection of direct sequence code division multiple access (OS-COMA) wireless communication systems. The main property of the proposed algorithm is its ability to resolve the multipath fading channel resulting in inter symbol interference (ISI) as well as multiple access interference (MAI). Other remarkable properties are its low complexity and mitigation to the near-far problem as well as its insensitivity to asynchronous transmission. The proposed system is based on the minimization of the output energy and convergence to the minimum mean square error (MMSE) detector. It is blind in the sense that it needs no knowledge of the other users' signatures, only the intended user signature and timing are required. Furthermore, the convergence of the minimum output energy (MOE) detector to the MMSE detector is analytically proven in case of M-ary PSK. Depicted results show that the performance of the generalized system dominates those previously considered. Further improvements are obtained when multiple input multiple output (MIMO) technique is employed.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.565-569
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• 1993

In this paper, a specified number of actuators are selected from a given set of admissible actuators. The selected set of actuators is likely to use minimum control energy while required output variance constraints are guaranteed to be satisfied. The actuator selection procedure is an iterative algorithm composed of two parts; an output variance constrained control and an input variance constrained control algorithm. The idea behind this algorithm is that the solution to the first control problem provides the necessary weighting matrix in the objective function of the second optimization problem, and the sensitivity information from the second problem is utilized to delete one actuator. For variance constrained control problems, by considering a dual version of each control problem an efficient algorithm is provided, whose convergence properties turn out to be better than an existing algorithm. Numerical examples with a simple beam are given for both the input/output variance constrained control problem and the actuator selection problem.

• Journal of Advanced Navigation Technology
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• v.16 no.6
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• pp.960-967
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• 2012

Wireless sensor network is used at the environment to obtain nearby information and since such information is transferred through wireless link, it causes unnecessary re-sending and disadvantage of big energy consumption at node. Because of this to select reliable, energy effective link, method of estimating quality on wireless link using RSSI(received signal strength indication), LQI(link quality indication), etc is needed on wireless link. To set up path extending survival time by reducing energy consumption of nodes at the wireless sensor network, the thesis selects with small standard deviation of LQI after obtaining LQI within each path. Additionally, LQI standard deviation routing algorithm is compared based on LQI algorithm such as minimum-LQI, hop-LQI weight and RF output -7dBm. According to the outcome, the algorithm suggested has superior characters such as the number of node, retransmission rate and network life span respectively compared to existing algorithm. Therefore, energy consumption can be efficiently reduced in case that LQI standard deviation routing scheme suggested by this paper is adapted to wireless sensor network.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.9
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• pp.1199-1205
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• 2014

A power system configuration has been increasingly advanced with a number of generating units. In particular, renewable energy resources are widely introduced due to the environmental issues. When applying the renewable energy sources with the ESS (Energy Storage System), the ESS is the role of a potential generating resource in the power system while mitigating the output volatility of renewable energy resources. Thus, for applications of the ESS, the surrounding environment of it should be considered, which means that capacity and energy of the ESS can be affected. Moreover, operation strategy of the ESS should be proposed according to the installation purpose as well as the surrounding environment. In the paper, operation strategy of the ESS is proposed considering load demand and the output of renewable energy resources on a hourly basis. Then, the cost of electrical energy is minimized based on the economic model that consists of capital cost, operation cost, fuel cost, and grid cost for a year. It is sure that peak-shaving effects can be achieved while satisfying the minimum cost of electrical energy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.6
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• pp.2686-2708
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• 2020

This paper investigates the energy efficiency of energy harvesting (EH) bidirectional cooperative sensor networks, in which the considered system model enables the uplink information transmission from the sensor (SN) to access point (AP) and the energy supply for the amplify-and-forward (AF) relay and SN using power-splitting (PS) or time-switching (TS) protocol. Considering the minimum EH activation constraint and quality of service (QoS) requirement, energy efficiency is maximized by jointly optimizing the resource division ratio and transmission power. To cope with the non-convexity of the optimizations, we propose the low complexity iterative algorithm based on fractional programming and alternative search method (FAS). The key idea of the proposed algorithm first transforms the objective function into the parameterized polynomial subtractive form. Then we decompose the optimization into two convex sub-problems, which can be solved by conventional convex programming. Simulation results validate that the proposed schemes have better output performance and the iterative algorithm has a fast convergence rate.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.876-881
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• 2006

In this paper, we propose a complex-valued IIR filter for digital VSB signals based on CMA in order to efficiently mitigate multipath distortions, especially the leakage from the quadrature component. The proposed equalizer overcomes the drawback of the conventional real-valued IIR equalizers that it attempts to equalize Hilbert transform of quadrature component. We demonstrate via simulation that the proposed complex IIR filter successfully mitigates the leakages from the quadrature component, while the conventional real IIR filter requires a longer IIR filter to achieve the same performance. We present cost function analysis for a simple two-tap case showing that the proposed IIR equalizer with CMA for VSB signals has a global minimum at the desired location.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.35 no.9
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• pp.380-387
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• 1986

We have developed a dual control algorithm by means of innovations approach and established the stability of dual by introducing the pole-placement method suggested by Berger on the non-dual control. The dual controller realizing this algorithm decreases control loss sharply when compared with that of a non-dual controller, and shows the characteristics of suppressing the output deviation in transient state effectively. The total control energy and the accumulated square misdistance of this dual controller are shown to be 1-10% and 0.1-10% of those of CE control, respectively. Consequently this controller solves the non-minimum phase problem encountered when discretizing the system equation, and can be used to overcome the uncertainty of system effectively by adjusting the learning rate of the controller.

• Journal of Institute of Control, Robotics and Systems
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• v.4 no.4
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• pp.448-457
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• 1998

A neural network based control algorithm with fuzzy compensation is proposed for the automated adjustment in the production of electronic end-products. The process of adjustment is to tune the variable devices in order to examine the specified performances of the products ready prior to packing. Camcorder is considered as a target product. The required test and adjustment system is developed. The adjustment system consists of a NNC(neural network controller), a sub-NNC, and an auxiliary algorithm utilizing the fuzzy logic. The neural network is trained by means of errors between the outputs of the real system and the network, as well as on the errors between the changing rate of the outputs. Control algorithm is derived to speed up the learning dynamics and to avoid the local minima at higher energy level, and is able to converge to the global minimum at lower energy level. Many unexpected problems in the application of the real system are resolved by the auxiliary algorithms. As the adjustments of multiple items are related to each other, but the significant effect of performance by any specific item is not observed. The experimental result shows that the proposed method performs very effectively and are advantageous in simple architecture, extracting easily the training data without expertise, adapting to the unstable system that the input-output properties of each products are slightly different, with a wide application to other similar adjustment processes.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.4
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• pp.717-725
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• 2011

In the power system with an electric storage system that can increase utilization rate of the source of such new renewable energy, this paper introduces the approach on the daily unit commitment scheduling that determines simultaneously optimum operational condition and output of thermal generators and electric storage device. The unit commitment is one of the most important issues in economic operation and security of short-term operational plan of the power system. It is to determine on/off status of generator to minimize operational cost during the given period. The committed generator should satisfy various operational limitation such as estimated demand by system, spinning reserve condition within minimum operational cost. In order to determine on/off or charge/discharge/idle condition and output level of units and electric storage system, the MILP(Mixed Integer Linear Programming) is suggested. The proposed approach is the mixed method between LP(Linear Programming) and IP(integer programming) which seeks the value of real number and integer that maximize or minimize function objective within given condition. The daily unit commitment problem with the electric storage system is applied to MILP algorithm through linearization and formulation process. The proposed approach is applied to the test system.