• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.4
• /
• pp.26-33
• /
• 2010

This paper presents a multi-channel capacitive touch sensing unit for SoC applications. This unit includes a simple common processing unit and switch array to detect the touch sensing input by capacitive-time(C-T) conversion method. This touch sensor ASIC is designed based on the Capacitive-Time(C-T) conversion method to have advantages of small current and chip area, and the minimum resolution of the unit is 41 fF per count with the built-in sensing oscillator, LDO regulator and $I^2C$ for no additional external components. This unit is implemented in 0.18 um CMOS process with dual supply voltage of 1.8 V and 3.3 V. The total power consumption of the unit is 60 uA and the area is 0.26 $mm^2$.

• 한국정보디스플레이학회:학술대회논문집
• /
• 2008.10a
• /
• pp.1503-1506
• /
• 2008

A novel white-LED (light emitting diode) backlight system for 46"LCD TVs which involves the current controlled X-Y channel driving method is proposed in this paper. There are two problems related to the LED current in the conventional X-Y channel driving driven by a constant voltage source. To solve these problems, a real time current sensing system is applied to the conventional one and the time-division current sensing method is employed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.3
• /
• pp.984-996
• /
• 2014

In this paper, optimal sensing time allocation for adaptive multiband spectrum sensing-transmission procedure is investigated. The sensing procedure consists of an exploration phase and a detection phase. We first formulate an optimization problem to maximize the throughput by designing not only the overall sensing time, but also the sensing time for every stage in the exploration and detection phases, while keeping the miss detection probability for each channel under a pre-defined threshold. Then, we transform the initial non-convex optimization problem into a convex bilevel optimization problem to make it mathematically tractable. Simulation results show that the optimized sensing time setting in this paper can provide a significant performance gain over the previous studies.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.9 no.8
• /
• pp.2755-2773
• /
• 2015

Cooperative spectrum sensing increases the detection performance in a cognitive radio network, based on the number of sensing nodes. However, as the number of sensing nodes increases, the reporting overhead linearly increases. This paper proposes two kinds of cooperative spectrum sensing with limited reporting in a centralized cognitive radio network, a soft combination with threshold-based reporting (SC-TR) and a soft combination with contention-based reporting (SC-CR). In the proposed SC-TR scheme, each sensing node reports its sensing result to the fusion center through its own reporting channel only if the observed energy value is higher than a decision threshold. In the proposed SC-CR scheme, sensing nodes compete to report their sensing results via shared reporting channels. The simulation results show that the proposed schemes significantly reduce the reporting overhead without sacrificing the detection performance too much.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.36 no.3A
• /
• pp.287-295
• /
• 2011

Cognitive radio (CR) features opportunistic access to spectrum when licensed users (LU) are not operating. To avoid interference to LU, cognitive users (CU) need to perform spectrum sensing. Because of local shadowing, fading, or limited sensing capability, it is suggested that multiple CUs cooperate to detect LU. In cooperative spectrum sensing, CUs should exchange their sensing data with minimum bandwidth and delay. In this paper, we introduce a novel method to efficiently report sensing data to the central node in an infrastructured OFDM-based CR network. All CUs simultaneously report their sensing data over unique and orthogonal signals on locally available subcarriers. By detecting the signals, the central node can determine subcarrier availability for each CU. Implementation challenges are identified and then their solutions are suggested. The proposed method is evaluated through simulation on a realistic channel model. The results show that the proposed method is feasible and efficient.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.25 no.5
• /
• pp.542-547
• /
• 2014

When a primary user transmits over some frequency band assigned to it, most of its transmission power tends to be concentrated in the band but a small portion of it spreads into the adjacent bands. Thus the false alarm probability for the adjacent bands can be higher than expected, even though no primary users are active in the bands. A previous work evaluated the effects of the adjacent channel leakage on the performance of an energy detection based spectrum sensing but it did not take into account the fading phenomenon. In this paper, we analyze the effects of the adjacent channel leakage on an energy detection based spectrum sensing scheme in terms of detection probability and false alarm probability in a fading environment.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.6
• /
• pp.3029-3045
• /
• 2017

The main processes of a cognitive radio system include spectrum sensing, spectrum decision, spectrum sharing, and spectrum conversion. Experimental results show that these stages introduce a time delay that affects the spectrum sensing accuracy, reducing its efficiency. To reduce the time delay, the frequency spectrum prediction was proposed to alleviate the burden on the spectrum sensing. In this paper, the deep recurrent neural network (DRNN) was proposed to predict the spectrum of multiple time slots, since the existing methods only predict the spectrum of one time slot. The continuous state of a channel is divided into a many time slots, forming a time series of the channel state. Since there are more hidden layers in the DRNN than in the RNN, the DRNN has fading memory in its bottom layer as well as in the past input. In addition, the extended Kalman filter was used to train the DRNN, which overcomes the problem of slow convergence and the vanishing gradient of the gradient descent method. The spectrum prediction based on the DRNN was verified with a WiFi signal, and the error of the prediction was analyzed. The simulation results proved that the multiple slot spectrum prediction improved the spectrum efficiency and reduced the energy consumption of spectrum sensing.

• Proceedings of the KSRS Conference
• /
• 2004.10a
• /
• pp.140-143
• /
• 2004

The west coast of the Korean Peninsula is famous for its large tidal range (up to 9 m) and vast tidal flats. With comparison the sedimentary environments of open and close tidal flat using remote sensing, we select Kanghwa tidal flat and Hwang-Do tidal flat in Cheonsu Bay. Prior to surface sediment discrimination using remote sensing, sedimentary environments including intertidal OEM, hydraulic condition, and relationship between grain size and various tidal condition are investigated. Remote sensing has the potential to provide synoptic information of intertidal environments. The objectives of this study are: (i) to generate an intertidal digital elevation model (OEM) using the waterline method of Lansat TM/ETM+, (ii) to investigate the tidal channel distribution using texture analysis, and (iii) to analyze the relationship between surface grain size by using in-situ data and intertidal OEM and tidal channel density by using high-resolution satellite data such as IKONOS and Kompsat EOC. The results demonstrate that satellite remote sensing is an efficient and effective tool for a surface sediment discrimination and long term morphologic change estimation in tidal flats.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2128-2147
• /
• 2021

Cognitive radio systems are being implemented recently to tackle spectrum underutilization problems and aid efficient data traffic. Spectrum sensing is the crucial step in cognitive applications in which cognitive user detects the presence of primary user (PU) in a particular channel thereby switching to another channel for continuous transmission. In cognitive radio systems, the capacity to precisely identify the primary user's signal is essential to secondary user so as to use idle licensed spectrum. Based on the inherent capability, a new spectrum sensing technique is proposed in this paper to identify all types of primary user signals in a cognitive radio condition. Hence, a spectrum sensing algorithm using improved convolutional neural network and long short-term memory (CNN-LSTM) is presented. The principle used in our approach is simulated annealing that discovers reasonable number of neurons for each layer of a completely associated deep neural network to tackle the streamlining issue. The probability of detection is considered as the determining parameter to find the efficiency of the proposed algorithm. Experiments are carried under different signal to noise ratio to indicate better performance of the proposed algorithm. The PU signal will have an associated modulation format and hence identifying the presence of a modulation format itself establishes the presence of PU signal.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.22 no.4
• /
• pp.423-429
• /
• 2011

Cooperative spectrum sensing is proposed to overcome some problem such as multipath fading and shadowing and to improve spectrum sensing performance. There are different combining methods for cooperative spectrum sensing: hard decision method and soft decision method. In this paper, we analysis the performance of cooperative spectrum sensing with distance based weight that is kind of a soft decision rule for cognitive radio(CR) systems and CR systems sense the spectrum of the licensed user by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate(CFAR) algorithm for energy detection. The signal of licensed user is OFDM signal and the wireless channel between a licensed user and CR systems is modeled as Gaussian channel. From the simulation results, the cooperative spectrum sensing with distance based weight combining(DWC) and equal gain combing(EGC) methods shows higher spectrum sensing performance than single spectrum sensing does. And the detection probability performance with the DWC is higher than that with the EGC.