• Journal of Institute of Control, Robotics and Systems
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• v.22 no.3
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• pp.199-203
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• 2016

A brain-computer interface or BCI provides an alternative method for acting on the world. Brain signals can be recorded from the electrical activity along the scalp using an electrode cap. By analyzing the EEG, it is possible to determine whether a person is thinking about his/her hand or foot movement and this information can be transferred to a machine and then translated into commands. However, we do not know which information relates to motor imagery and which channel is good for extracting features. A general approach is to use all electronic channels to analyze the EEG signals, but this causes many problems, such as overfitting and problems removing noisy and artificial signals. To overcome these problems, in this paper we used a new optimization method called the Fruit Fly optimization algorithm (FOA) to select the best channels and then combine them with CSP method to extract features to improve the classification accuracy by linear discriminant analysis. We also used particle swarm optimization (PSO) and a genetic algorithm (GA) to select the optimal EEG channel and compared the performance with that of the FOA algorithm. The results show that for some subjects, the FOA algorithm is a better method for selecting the optimal EEG channel in a short time.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.1
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• pp.58-71
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• 2019

This paper proposes architecture of a cognitive radio engine platform and the allowable frequency channel reasoning method that enables acquisition of the allowable channels for the military tactical network environment. The current military tactical wireless communication system is increasing need to secure a supplementary radio frequency to ensure that multiple wireless networks for different military wireless devices coexist, so that tactical wireless communication between the same or different systems can be operated effectively. This paper presents the allowable frequency channel reasoning method based on cognitive radio engine for realizing DSA(Dynamic Spectrum Access) as an optimal available frequency channel. To this end, a case-based allowable frequency channel reasoning method for cognitive radio devices is proposed through modeling of primary user's traffic status and calculation of channel occupancy probability. Also through the simulation of the performance analysis, changing rate of collision probability between the primary users' occupancy channel and the available channel acquisition information that can be used by the cognitive radio device was analysed.

• ETRI Journal
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• v.40 no.3
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• pp.291-302
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• 2018

The deployment of an incremental hybrid decode-amplify and forward relaying scheme is a promising and superior solution for cellular networks to meet ever-growing network traffic demands. However, the selection of a suitable relaying protocol based on the signal-to-noise ratio threshold is important in realizing an improved quality of service. In this paper, an incremental hybrid relaying protocol is proposed using polar codes. The proposed protocol achieves a better performance than existing turbo codes in terms of capacity. Simulation results show that the polar codes through an incremental hybrid decode-amplify-and-forward relay can provide a 38% gain when ${\gamma}_{th(1)}$ and ${\gamma}_{th(2)}$ are optimal. Further, the channel capacity is improved to 17.5 b/s/Hz and 23 b/s/Hz for $2{\times}2$ MIMO and $4{\times}4$ MIMO systems, respectively. Monte Carlo simulations are carried out to achieve the optimal solution.

• ETRI Journal
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• v.40 no.2
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• pp.237-245
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• 2018

The Distributed Modulated Wideband Converter (DMWC) is a networking system developed from the Modulated Wideband Converter, which converts all sampling channels into sensing nodes with number variables to implement signal undersampling. When the number of sparse subbands changes, the number of nodes can be adjusted flexibly to improve the reconstruction rate. Owing to the different attenuations of distributed nodes in different locations, it is worthwhile to find out how to select the optimal sensing node as the sampling channel. This paper proposes the spectrum sensing of DMWC based on a Markov random field (MRF) to select the ideal node, which is compared to the image edge segmentation. The attenuation of the candidate nodes is estimated based on the attenuation of the neighboring nodes that have participated in the DMWC system. Theoretical analysis and numerical simulations show that neighboring attenuation plays an important role in determining the node selection, and selecting the node using MRF can avoid serious transmission attenuation. Furthermore, DMWC can greatly improve recovery performance by using a Markov random field compared with random selection.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.7
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• pp.1597-1601
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• 2013

Multiple antenna technique is attracting attention as a core technology for next-generation mobile communication systems to accommodate explosively increasing mobile data traffic. Especially, recent researches focus on multi-user multiple input multiple output (MU-MIMO) system where base stations are equipped with several tens of transmit antennas and transmit data to multiple terminals (users) simultaneously. To enhance the performance of MU-MIMO systems, we, in this paper, propose an adaptive user selection algorithm which adaptively selects a user set according to varying channel states. According to Monte-Carlo based computer simulations, the performance of proposed scheme is significantly improved compared to the conventional scheme without user selection and approaches that of exhaustive search-based optimal scheme. On the other hand, the proposed scheme can reduce the computational complexity to $K/(2^K-1)$ compared to the optimal scheme where K denotes the number of total users.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.2
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• pp.618-633
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• 2014

Relay technology is becoming more important for mobile communications and wireless internet of things (IoT) networking because of the extended access network coverage range and reliable quality of service (QoS) it can provide at low power consumption levels. Existing mobile multihop relay (MMR) technology uses fixed-point stationary relay stations (RSs) and a divided time-frame (or frequency-band) to support the relay operation. This approach has limitations when a local fixed-point stationary RS does not exist. In addition, since the time-frame (or frequency-band) channel resources are pre-divided for the relay operation, there is no way to achieve high channel utilization using intelligent opportunistic techniques. In this paper, a different approach is considered, where the use of mobile/IoT devices as RSs is considered. In applications that use mobile/IoT devices as relay systems, due to the very limited battery energy of a mobile/IoT device and unequal channel conditions to and from the RS, both minimum energy consumption and QoS support must be considered simultaneously in the selection and configuration of RSs. Therefore, in this paper, a mobile RS is selected and configured with the objective of minimizing power consumption while satisfying end-to-end data rate and bit error rate (BER) requirements. For the RS, both downlink (DL) to the destination system (DS) (i.e., IoT device or user equipment (UE)) and uplink (UL) to the base station (BS) need to be adaptively configured (using adaptive modulation and power control) to minimize power consumption while satisfying the end-to-end QoS constraints. This paper proposes a minimum transmission power consuming RS selection and configuration (MPRSC) scheme, where the RS uses cognitive radio (CR) sub-channels when communicating with the DS, and therefore the scheme is named MPRSC-CR. The proposed MPRSC-CR scheme is activated when a DS moves out of the BS's QoS supportive coverage range. In this case, data transmissions between the RS and BS use the assigned primary channel that the DS had been using, and data transmissions between the RS and DS use CR sub-channels. The simulation results demonstrate that the proposed MPRSC-CR scheme extends the coverage range of the BS and minimizes the power consumption of the RS through optimal selection and configuration of a RS.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.12
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• pp.1220-1225
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• 2010

This paper proposes a novel active noise control (ANC) approach that uses an IIR filter and neural network techniques to effectively reduce interior noise. We construct a multiple-channel IIR filter module which is a linearly augmented framework with a generic IIR model to generate a primary control signal. A three-layer perceptron neural network is employed for establishing a secondary-path model to represent air channels among noise fields. Since the IIR module and neural network are connected in series, the output of an IIR filter is transferred forward to the neural model to generate a final ANC signal. A gradient descent optimization based learning algorithm is analytically derived for the optimal selection of the ANC parameter vectors. Moreover, re-estimation of partial parameter vectors in the ANC system is proposed for online learning. Lastly, we present the results of a numerical study to test our ANC methodology with realistic interior noise measurement obtained from Korean railway trains.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.8A
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• pp.601-611
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• 2012

In this paper, we first study the spatial multiplexing gain for the 3-cell interfering broadcast channels (IFBC) where all base stations and mobile users are equipped with multiple antennas. Then, we present the IA scheme in conjunction with user selection which outperforms the TDMA technique in the IFBC environment. The optimal scheduling method utilizes multiuser diversity to achieve a significant fraction of sum capacity by using an exhaustive search algorithm. To reduce the computational complexity, a suboptimal scheduling method is proposed based on a coordinate ascent approach.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.9
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• pp.3034-3055
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• 2014

Wireless Sensor Networks have extensively been utilized for ambient data collection from simple linear structures to dense tiered deployments. Issues related to optimal resource allocation still persist for simplistic deployments including linear and hierarchical networks. In this work, we investigate the case of dimensioning parameters for linear and tiered wireless sensor network deployments with notion of providing extended lifetime and reliable data delivery over extensive infrastructures. We provide a single consolidated reference for selection of intrinsic sensor network parameters like number of required nodes for deployment over specified area, network operational lifetime, data aggregation requirements, energy dissipation concerns and communication channel related signal reliability. The dimensioning parameters have been analyzed in a pipeline monitoring scenario using ZigBee communication platform and subsequently referred with analytical models to ensure the dimensioning process is reflected in real world deployment with minimum resource consumption and best network connectivity. Concerns over data aggregation and routing delay minimization have been discussed with possible solutions. Finally, we propose a node placement strategy based on a dynamic programming model for achieving reliable received signals and consistent application in structural health monitoring with multi hop and long distance connectivity.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.4 s.119
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• pp.440-447
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• 2007

The switched diversity, although its performance is a little inferior to the selection diversity, is widely used due to its advantage that only one RF circuit is required for its operation without respect to the number of antennas in use. In this paper, we propose an application of the antenna switched diversity to a spread spectrum system with adaptive modulation and derived the optimal antenna switching threshold to maximize the average transmission bit rate. We also compared the performances of the proposed system with those of the two cases using a single antenna and the selection diversity with two antennas in terms of the average number of bits per symbol(BPS), the probability of no transmission, and the average BER. The performance analysis shows that, if the number of paths in a multipath channel environment increases, the performance of the proposed scheme becomes closer to that of the selection diversity based system in terms of the average BPS. Furthermore, the proposed scheme produces as almost high the probability of no transmission as the selection diversity based system for the case of low average SNR, although the former yields a little higher probability of no transmission than the latter fer the case of high average SNR.