• Proceedings of the Korean Information Science Society Conference
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• 2006.10d
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• pp.18-23
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• 2006

높은 데이터 전송률과 넓은 전송 대역을 제공할 수 있도록 표준화 된 시스템인 IEEE 802.16d[1]시스템에서는 여러 가지 서비스 클래스들을 이용하여 QoS를 보장해 줄 수 있을 것으로 기대하고 있다. 그러나, 효율적인 QoS를 제공하기 위해서는 스케줄링에 필요한 factor들을 적절하게 설정해야 하며, 시스템의 환경에 맞도록 변경해야 한다. 따라서, 본 논문에서는 IEEE 802.16d 시스템을 simulator (NS-2) [2]에 구현하고, IEEE 802.16f [3]에서 표준화한 MIB과 QoS를 고려한 MIB (Q-MAN MIB)을 구현하여 IEEE 802.16d 시스템과 연동하도록 구축한 네트워크 관리 시스템인 Q-MAN을 소개한다. Q-MAN 네트워크 관리 시스템을 통해 IEEE 802.16d 시스템의 QoS 제공 상태에 대한 모니터링이 가능하고, 스케줄링에 필요한 설정 값을 동적으로 변경이 가능하기 때문에 IEEE 802.16d 시스템의 효율을 극대화 시킬 수 있다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.1A
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• pp.115-124
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• 2007

In this paper, the I/Q mismatch problem between the transmission line and antenna switch is solved by a new CPW matching circuit for a VoWLAN terminal with 54 Mbps communication speed through the IEEE 802.11 b/g CCK/OFDM. I/Q performances with the new matching circuit are analyzed and improved by the output spectrum mask, the characteristics of the EVM(Error Vector Magnitude) due to the nonlinear CCK/OFDM demodulation data, and receiver's sensitivity.

• Journal of Korea Society of Digital Industry and Information Management
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• v.16 no.1
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• pp.11-19
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• 2020

IoT has been consistently used in various fields such as smart home, wearables, and healthcare. Since IoT devices are small terminals, relatively simple wireless communication protocols such as IEEE 802.15.4 and ISO 18000 series are used. In this paper, we designed the 802.15.4q 2.4 GHz TASK physical layer. Physical protocol data unit of TASK supports bit-level interleaving and shortened BCH encoding. It is spread by unique ternary sequences. There are four spreading factors to choose the data rate according to the communication channel environment. The TASK physical layer was designed using verilog-HDL and verified through the loop-back test of the transceiver. The designed TASK physical layer was implemented in a fpga and tested using MAXIM RFICs. The PER was about 0% at 10 dB SNR. It is expected to be used in small, low power IoT applications.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1923-1928
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• 2010

The IEC 61850 protocol proposed for the interoperability between IEDs(intelligent electronic devices) adopts the prioritized switched ethernet as its communication channel because substation bus is utilized to exchange both real-time and non real-time messages. The prioritized switched ethernet uses IEEE 802.1Q/p QoS(Quality of Service) in addition to IEEE 802.3 ethernet to enhance the real-time characteristics. However, IEEE 802.1Q/p QoS has priority-blocking problem that occurs when higher-priority frame transmission request during lower-priority frame transmission. To resolve this problem, this paper proposes P(Preemptive)-Ethernet. P-Ethernet uses the modified IEEE 802.1Q/p frame format and new priority preemption mechanism. This paper also implements P-Ethernet controller using FPGA (Virtex-4) and MicroBlaze processor. From the implementation results, P-Ethernet controller shows a improved latency and jitter of transmission period compare to the normal ethernet controller.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.1 s.343
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• pp.49-56
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• 2006

This paper describes the design and the verification of IEEE 802.15.4 LR-WPAN 2.4GHz Physical layer for Ubiquitous Sensor Network(USN). We designed the Carrier Frequency Offset(CFO) compensation satisfied the frequency tolerance of IEEE 802.15.4 LR-WPAN and the adaptive matched filter that re-setting of the threshold for the symbol synchronization of the various USN environment. The multiplications is reduced 1/16 by this method each other at i, q phases and has 0.5dB performance improvement in detection probability. Proposed baseband system is designed with verilog HDL and implemented using FPGA prototype board.

• Journal of information and communication convergence engineering
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• v.19 no.1
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• pp.1-7
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• 2021

Reinforcement learning is an area of machine learning that studies how an intelligent agent takes actions in a given environment to maximize the cumulative reward. In this paper, we propose a new MAC protocol based on the Q-learning technique of reinforcement learning to improve the performance of the IEEE 802.11 wireless LAN CSMA/CA MAC protocol. Furthermore, the operation of each access point (AP) and station is proposed. The AP adjusts the value of the contention window (CW), which is the range for determining the backoff number of the station, according to the wireless traffic load. The station improves the performance by selecting an optimal backoff number with the lowest packet collision rate and the highest transmission success rate through Q-learning within the CW value transmitted from the AP. The result of the performance evaluation through computer simulations showed that the proposed scheme has a higher throughput than that of the existing CSMA/CA scheme.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.3
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• pp.51-57
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• 2010

A dual-mode direct conversion receiver is developed in $0.13\;{\mu}m$ RF CMOS process for IEEE 802.11n based wireless LAN and IEEE 802.16e based mobile WiMAX application. The RF receiver covers the frequency band between 2.3 and 2.7 GHz. Three-step gain control is realized in LNA by using current steering technique. Current bleeding technique is applied to the down-conversion mixer in order to lower the flicker noise. A frequency divide-by-2 circuit is included in the receiver for LO I/Q differential signal generation. The receiver consumes 56 mA at 1.4 V supply voltage including all LO buffers. Measured results show a power gain of 32 dB, a noise figure of 4.8 dB, a output $P_{1dB}$ of +6 dBm over the entire band.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.334-349
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• 2022

The effectiveness of Wi-Fi networks is greatly influenced by the optimization of contention window (CW) parameters. Unfortunately, the conventional approach employed by IEEE 802.11 wireless networks is not scalable enough to sustain consistent performance for the increasing number of stations. Yet, it is still the default when accessing channels for single-users of 802.11 transmissions. Recently, there has been a spike in attempts to enhance network performance using a machine learning (ML) technique known as reinforcement learning (RL). Its advantage is interacting with the surrounding environment and making decisions based on its own experience. Deep RL (DRL) uses deep neural networks (DNN) to deal with more complex environments (such as continuous state spaces or actions spaces) and to get optimum rewards. As a result, we present a new approach of CW control mechanism, which is termed as contention window threshold (CW_Threshold). It uses the DRL principle to define the threshold value and learn optimal settings under various network scenarios. We demonstrate our proposed method, known as a smart exponential-threshold-linear backoff algorithm with a deep Q-learning network (SETL-DQN). The simulation results show that our proposed SETL-DQN algorithm can effectively improve the throughput and reduce the collision rates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.5A
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• pp.502-513
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• 2004

This paper proposes a symbol synchronization method in the IEEE 802.11a wireless OPDM system, which uses only signs of the in-phase and the quadrature signals in the short preamble. The short preamble is sampled with 2 tines of Nyquist sampling rate and both of the autocorrelation and the cross-relation are used in the proposed method. This method has some advantages that the ACG (Automatic Gain Control) can be processed concurrently during the short preamble and its implementation is not much complicated. The proposed symbol synchronization method is verified through simulations on frequency offset, multi-path and white Gaussian noise.

• Journal of Computing Science and Engineering
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• v.8 no.3
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• pp.129-136
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• 2014

This paper presents the equivalent circuit modelling and eigenfrequency analysis of a wideband robust capacitive radio frequency (RF) microelectromechanical system (MEMS) switch that was designed using Poly-Si and Au layer membrane for highly reliable switching operation. The circuit characterization includes the extraction of resistance, inductance, on and off state capacitance, and Q-factor. The first six eigenfrequencies are analyzed using a finite element modeler, and the equivalent modes are demonstrated. The switch is optimized for millimeter wave frequencies, which indicate excellent RF performance with isolation of more than 55 dB and a low insertion loss of 0.1 dB in the V-band. The designed switch actuates at 13.2 V. The R, L, C and Q-factor are simulated using Y-matrix data over a frequency sweep of 20-100 GHz. The proposed switch has various applications in satellite communication networks and can also be used for devices that will incorporate the upcoming IEEE Wi-Fi 802.11ad protocol.