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In this work, we consider a secure precoding optimization problem for the artificial noise (AN) scheme in multiple-input single-output (MISO) wiretap channels. In previous researches (Lin et al. , 2013), it was proved that the generalized AN scheme which allows some portion of AN signal to be injected to the legitimate receiver's channel is the optimal precoding scheme for MISO wiretap channels. However, the optimality is valid only under some ideal assumptions such as perfect channel estimation and spatially uncorrelated channels. To break through this limitation, in this paper, we propose a novel deep neural network (DNN)-based secure precoding scheme, called the deep AN scheme. To the best of the authors’ knowledge, the deep AN scheme is the first secure precoding scheme which exploits a DNN to jointly design and optimize the precoders for the information signal and the AN signal. From the numerical experiments, it is demonstrated that the proposed deep AN scheme outperforms the generalized AN scheme under various practical wireless environments.

Ground vibration monitoring with microelectromechanical systems (MEMS) sensors is very effective and promising for alerting geological disasters. In this letter, explicitly considering and effectively addressing several specific issues related to practical MEMS sensors, we develop a novel ground vibration monitoring scheme for MEMS sensed data based on a deep convolutional neural network (CNN). Experiments are then conducted on the synthetic and real data sets. Experimental results on both data sets demonstrate that the proposed scheme significantly outperforms the other comparable schemes. For the synthetic data set, the proposed scheme achieves a very high overall accuracy of 98.82%. Also, for the real data set, the proposed scheme achieves a high overall accuracy of 81.64%, which is about 7% higher than that reported in the literature.

An experimental study on the resistance of concrete containing air-cooled slag (AS) and water-cooled slag (WS) against freeze–thaw cycles was conducted. For comparison, the durability of ASTM Type I ordinary Portland cement (OPC) concrete exposed to the same freeze–thaw environment was examined. To evaluate the durability of concrete exposed to the freeze–thaw environment, an experiment was conducted according to ASTM C 666 procedure A. Furthermore, the relative dynamic modulus of elasticity, surface electrical resistivity, and compressive strength of concrete specimens were measured after exposing them to freeze–thaw cycles for a predetermined period, and the results were compared with those of OPC concrete. The relationship between the freeze and thaw resistances of concrete and the air-void system (spacing factor and specific surface area) was identified. Furthermore, the microstructure of concrete exposed to freeze–thaw cycles was observed using scanning electron microscopy to identify the interfacial transition zone, cracks, and micropores. Experimental results showed that the resistance of blended cement concrete containing WS and AS against freeze–thaw cycles was significantly higher than that of OPC concrete. The concrete in which 10% of OPC was replaced by AS exhibited a similar durability as that of the concrete in which 40% of OPC was replaced only by WS. Therefore, it is expected that blended cement concrete containing WS and AS based on an appropriate mix proportion design will exhibit excellent durability in regions experiencing freezing temperatures.

In this letter, we propose a joint pilot design and channel estimation scheme based on the deep learning (DL) technique for multiuser multiple-input multiple output (MIMO) channels. To this end, we construct a pilot designer using two-layer neural networks (TNNs) and a channel estimator using deep neural networks (DNNs), which are jointly trained to minimize the mean square error (MSE) of channel estimation. To effectively reduce the interference among the multiple users, we also use the successive interference cancellation (SIC) technique in the channel estimation process. The numerical results demonstrate that the proposed scheme considerably outperforms the linear minimum mean square error (LMMSE) based channel estimation scheme.

In this letter, we propose a deep learning (DL)-based channel estimation scheme for the massive multiple-input multiple-output (MIMO) system. Unlike existing studies, we develop the channel estimation scheme for the case that the pilot length is smaller than the number of transmit antennas. The proposed scheme takes a two-stage estimation process: 1) a DL-based pilot-aided channel estimation and 2) a DL-based data-aided channel estimation. In the first stage, the pilot itself and the channel estimator are jointly designed by using both a two-layer neural network (TNN) and a deep neural network (DNN). In the second stage, the accuracy of channel estimation is further enhanced by using another DNN in an iterative manner. The simulation results demonstrate that the proposed channel estimation scheme has much better performance than the conventional channel estimation scheme. We also derive a useful insight into the optimal pilot length given the number of transmit antennas.

We study the joint transmit (Tx) power allocation and receive (Rx) power splitting for simultaneous wireless information and power transfer (SWIPT). Considering the practical scenario of nonlinear energy harvesting (EH), we adopt the realistic nonlinear EH model for analysis. To address the critical nonlinearity issue due to the saturation, we propose to use multiple EH circuits in parallel. An important problem is to maximize the achievable rate by jointly optimizing Tx power allocation and Rx power splitting, which is a nonconvex problem. In this paper, we first derive the optimal solution for any number of EH circuits. Then we study how the number of EH circuits required to avoid the saturation should be determined. From the obtained results, we draw useful and interesting insights into the SWIPT system with nonlinear EH. Numerical results demonstrate that employing multiple EH circuits substantially enhances the SWIPT performance with nonlinear EH., Comment: 4 pages, 1 figure

In this letter, we propose a new adaptive rate and energy harvesting interval control scheme to maximize the throughout subject to the average energy constraint in the multiple-input single-output simultaneous wireless information and power transfer system. We consider the realistic scenario of time-varying fading channel. In order to maximize the throughput and simultaneously to maintain the average energy required at the receiver, we first formulate a problem of jointly optimizing the rate and energy harvesting interval based on a Markov decision process (MDP) by using a regularization parameter. However, this MDP problem is difficult to directly solve because the channel transition probabilities (i.e., the model or the environment) are challenging to estimate in the practical systems. Thus, we propose an adaptive rate and energy harvesting interval control algorithm based on the model-free reinforcement learning technique. Numerical results demonstrate that the proposed scheme significantly outperforms the conventional scheme.

We propose a deep-learning-based channel estimation technique for wireless energy transfer. Specifically, we develop a channel learning scheme using the deep autoencoder, which learns the channel state information (CSI) at the energy transmitter based on the harvested energy feedback from the energy receiver, in the sense of minimizing the mean square error (mse) of the channel estimation. Numerical results demonstrate that the proposed scheme learns the CSI very well and significantly outperforms the conventional scheme in terms of the channel estimation mse as well as the harvested energy.

In this letter, we study the user grouping for the downlink nonorthogonal multiple access system. The optimal user grouping problem is formulated to maximize the sum rate. Due to the combinatorial nature, the computational complexity to find the optimal solution is generally very high. To address the complexity issue, we propose faster optimal and suboptimal schemes for the user grouping problem. We then obtain the useful and important insight of the optimal user grouping. Numerical results demonstrate that the proposed schemes significantly outperform the existing schemes and the proposed suboptimal algorithm works very close to the optimal algorithm.

In this paper, we study time-varying channel estimation and optimal pilot design for multiple-input multiple-output two-way multi-relay systems in the sense of minimizing the total estimation mean square error (MSE) under the power constraints at two source nodes and multiple relays. A particularly challenging issue in the optimal pilot design is to completely eliminate the inter-link interference while most efficiently using the channel resource. To address this challenging issue, we consider a pilot design approach based on the phase rotation technique at multiple relays. First, we establish various optimality conditions for the pilot design in the sense of the minimum total MSE. Then, we propose the optimal pilot scheme by designing the pilot signals, phase rotations, and pilot symbol positions to satisfy the established optimality conditions. Finally, we propose the asymptotically optimal pilot scheme in the high signal-to-noise ratio (SNR) regime with low complexity. Simulation results show that the proposed schemes significantly outperform the existing schemes in terms of the channel estimation and the bit error rate, and the proposed asymptotically optimal scheme provides the near-optimal performance even in the low to moderate SNR range.

In this paper, the problem of joint mode switching and power adaptation is studied for simultaneous wireless information and power transfer (SWIPT) over a fading channel. The receiver dynamically switches between information decoding (ID) and energy harvesting (EH) modes while the transmitter dynamically adapts the transmit power. Considering the nonlinearity of practical EH circuits, a realistic nonlinear EH model is adopted rather than the idealistic linear EH model. To characterize the ultimate performance tradeoff between ID and EH, an optimization problem is formulated to maximize the average harvested energy under the constraints on the average achievable rate and the average transmit power, which is a nonconvex and combinatorial problem. To solve this problem, first, the optimal power adaptation scheme for the nonlinear EH receiver that operates only in the EH mode is proposed. Using this scheme, the jointly optimal solution for the mode switching and power adaptation is then derived. By comparing the obtained results to the existing results, various useful and interesting insights into the optimized SWIPT system with nonlinear EH are presented. An important insight into the impact of nonlinear EH is that, to exploit the high energy conversion efficiency of the nonlinear circuit, the EH mode has to be selected only in the moderate range of channel gains. Also, in the EH mode, the power has to be adapted to the short-term power threshold only for the moderate channel gains.

In this paper, we study rate-energy (R-E) tradeoffs for simultaneous wireless information and power transfer (SWIPT). In the existing literature, by invoking a simplistic and ideal assumption of linear energy harvesting, the R-E tradeoff performance was analyzed only for the four SWIPT schemes: the dynamic power splitting, type-I on–off power splitting (OPS), static power splitting, and time switching. Different from such works, in this work, we consider the realistic and practical scenario of nonlinear energy harvesting. Furthermore, to characterize the R-E tradeoff with nonlinear energy harvesting, we propose a new SWIPT scheme, the generalized OPS (GOPS). As a special case of the proposed GOPS, we also investigate an additional SWIPT scheme, the type-II OPS. Through the analysis based on the realistic nonlinear models reported in the literature, we derive new theoretical results on the R-E tradeoff, which are in sharp contrast to those in the existing literature obtained with linear energy harvesting. Furthermore, we provide various useful insights into the SWIPT system with nonlinear energy harvesting.

In this paper, the fundamental performance of the simultaneous wireless information and power transfer (SWIPT) system is studied. Unlike any existing works where the codelength was assumed to be infinity, we explicitly consider the case of the finite codelength, which is much more realistic especially for the practical SWIPT system due to its limited power and complexity. For the four well-known SWIPT schemes, we analyze the tradeoff between the rate and energy; then we study the optimality of those SWIPT schemes. Furthermore, to fully characterize the fundamental performance of the SWIPT system in the regime of finite codelength, we propose to additionally use the new tradeoff between the decoding error probability and the harvested energy. In the sense of this new tradeoff, we study the optimality of the four SWIPT schemes. For the analysis of the two types of tradeoffs, we consider two different cases: when the transmit power of symbols is adapted or not. For various scenarios, we provide useful insights into the performance of the SWIPT system in the finite codelength.

The segregation potential (SP) is widely accepted in engineering design and for frost heave predictions, because it can be readily obtained in step-freezing laboratory tests. The SP at the onset of formation of the last ice lens (near the thermal steady-state condition, tp) in step-freezing tests is a representative value that applies in the field due to the low freezing rate there. The determination of tp is an essential prerequisite for obtaining a representative SP. However, it is difficult to determine when the thermal steady-state is achieved under freezing direction from bottom upwards for minimizing experimental error. Last ice lens (ice crystal) is elongated continuously even though the frost front reaches the center of the soil specimen by the boundary temperature conditions. Here, a frost ratio (Fz) is defined on the basis of the temperature profile with normalized specimen height. The tp is defined as being when the Fz reaches 90%, based on visual observation of the last ice lens formation. However, the determination of the representative SP may still involve a complicated analysis. This is alleviated here by a simple empirical logarithmic time-fitting method, without measuring the temperature profile across the soil specimen. The starting point of the tangential line in the heave curve with a logarithmic timescale empirically coincides with tp. The representative SP for engineering applications can then be easily determined with a simple frost heave testing method involving only total heave and cold–warm end temperatures.

A multiuser secure broadcast system is considered, where there are one multiantenna base station (BS), multiple single-antenna legitimate users, one multiantenna friendly jammer (FJ), and one multiantenna eavesdropper (Eve). We jointly design the optimal precoding matrix at the BS and the jamming covariance matrix at the FJ by minimizing the total transmit power of the BS and FJ under the signal-to-interference-plus-noise ratio constraints at the users and Eve. To solve this challenging problem, when the FJ has more antennas than the users and Eve, we first find the optimal structure of the jamming covariance matrix and, then, convert the problem into its equivalent convex form. Also, we propose an iterative algorithm to jointly design the precoding and jamming covariance matrices in all scenarios. The solution obtained by this algorithm is shown to be asymptotically optimal when the FJ has more antennas than the users and Eve. Numerical results show that the proposed schemes considerably outperform the existing schemes.

We study mode switching (MS) between information decoding and energy harvesting (EH) for simultaneous wireless information and power transfer (SWIPT) over the fading channel. Unlike the existing result obtained with a simplistic assumption of linear EH, we consider a realistic scenario of the nonlinear EH. In this setting, to design the optimal MS, we address the problem of maximizing the average achievable rate under an average harvested energy constraint, which is generally nonconvex and combinatorial. Using the time-sharing condition, the optimal MS solution for the nonlinear EH is presented efficiently. From the obtained result and further analysis, we draw interesting and important insights into the optimized SWIPT system with nonlinear EH.

In this paper, we study a training design problem for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) amplify-and-forward (AF) two-way relay networks. Unlike the existing studies, we assume the spatially correlated fading and consider the nonreciprocal channel condition, which is a more practical assumption but makes the training problem more challenging. The equivalent channels of bidirectional relaying links, which consist of self-interfering channels and information-bearing channels, are estimated at each source node based on a linear minimum mean square error (LMMSE) approach. The total mean square error (MSE) of the channel estimation is minimized under the transmit power constraints at the source nodes and at the relay. To solve this problem, we first derive an optimal structure of the training signals, and then, convert the optimization problem into a tractable convex form, from which the optimal training scheme is designed efficiently. Furthermore, for a practical special case, the optimal training design is derived in semi-closed form, which provides useful insights. To reduce the required complexity, a low-complexity training scheme is also derived in closed-form. This scheme is shown to be asymptotically optimal in the high signal-to-noise ratio (SNR) regime and gives further insights into the optimal training. The performance of the proposed schemes is demonstrated through numerical simulations.

Impact-echo method has been successfully used to detect flaws in concrete and to evaluate the state of grout bonding in tunnels. It has not yet been used to detect underground cavities formed by leakage of pipelines, which is becoming a major problem in many urban environments. We perform model and field tests to evaluate whether the impact-echo method can be used to detect cavities around concrete sewage pipelines. Fourier spectrum was used to determine the resonant frequency and the short time Fourier transform was used to determine the temporal variation of the resonant frequency component. Results show that the presence of cavity cannot be reliably predicted from the wave time history or Fourier spectrum. The spectrogram is demonstrated to be a better indicator for detecting the presence of a cavity. The cavity induces a longer tail in the spectrogram because of a higher impedance contrast and a lower attenuation. We propose a new quantitative index based on the resonant frequency and the spectrogram, denoted as the sustained duration. Both model and field tests demonstrate that the cavity in wet soils can be successfully detected using the proposed index.

There are numerous factors that affect stress distribution in a buried pipe, such as the shape, size, and stiffness of the pipe, its burial depth, and the stiffness of the surrounding soil. In addition, the pipe can benefit from the soil arching effect to some extent, through which the overburden and surcharge pressure at the crown can be carried by the adjacent soil. As a result, the buried pipe needs to support only a portion of the load that is not transferred to the adjacent soil. This paper presents numerical efforts to investigate the stress distribution in the buried concrete pipe under various environmental conditions. To that end, a nonlinear elasto-plastic model for backfill materials was implemented into finite element software by a user-defined subroutine (user material, or UMAT) to more precisely analyze the soil behavior surrounding a buried concrete pipe subjected to surface loading. In addition, three different backfill materials with a native soil were selected to examine the material-specific stress distribution in pipe. The environmental conditions considering in this study the loading effect and void effects were investigated using finite element method. The simulation results provide information on how the pressures are redistributed, and how the buried concrete pipe behaves under various environmental conditions.

In this letter, we present training designs for estimation of spatially correlated multiple-input multiple-output amplify-and-forward two-way multi-relay channels. An optimal training structure is initially derived to minimize total mean-square-error of the channel estimation and, then, source training power and relay amplification parameters are optimized numerically. For the purpose of complexity reduction and implementation simplicity, an upper bound-based power allocation is also proposed in a closed form. Simulation results show that the proposed schemes considerably outperform the conventional schemes.

Recently, people are increasingly interested in horizontal directional drilling (HDD) to construct oil and gas pipeline and utility pipeline in the urban area as one of trenchless methods. One of major issues during the HDD is the collapse of borehole, which may be the potential causes of ground collapse. This study investigated the effect of mud pressure on the borehole stability, using finite element analysis. Since the borehole is being drilled with a certain angle, three dimensional analysis should be performed. The borehole stability was examined by applying two different types of mud pressures, i.e., uniform and non-uniform, to the exterior surface of borehole. The results show that the high mud pressure at the beginning of drilling, i.e., at shallow depth, causes the borehole collapse, whereas the borehole was stable even at high mud pressure as the drilling depth increases. It can be said that the determination of maximum mud pressure is strongly related to the drilling depth.

We study the dynamic power splitting for simultaneous wireless information and power transfer (SWIPT) in the ergodic fading channel. Considering the nonlinearity of practical energy harvesting circuits, we adopt the realistic nonlinear energy harvesting (EH) model rather than the idealistic linear EH model. To characterize the optimal rate-energy (RE) tradeoff, we consider the problem of maximizing the R-E region, which is nonconvex. We solve this challenging problem for two different cases of the channel state information (CSI): (i) when the CSI is known only at the receiver (the CSIR case) and (ii) when the CSI is known at both the transmitter and the receiver (the CSI case). For these two cases, we develop the corresponding optimal dynamic power splitting schemes. To address the complexity issue, we also propose the suboptimal schemes with low complexities. Comparing the proposed schemes to the existing schemes, we provide various useful and interesting insights into the dynamic power splitting for the nonlinear EH. Furthermore, we extend the analysis to the scenarios of the partial CSI at the transmitter and the harvested energy maximization. Numerical results demonstrate that the proposed schemes significantly outperform the existing schemes and the proposed suboptimal scheme works very close to the optimal scheme at a much lower complexity., 15 pages, 5 figures

This letter proposes channel training designs for two-hop multi-relay networks, where a source, a destination and multiple amplify-and-forward (AF) relays are all equipped with multi-antenna, based on mean square error (MSE) and signal-to-noise ratio (SNR) criteria with taking into account spatial fading correlation between multiple-input multiple-output (MIMO) channel elements. The minimum MSE and maximum SNR channel estimators are initially derived and, then, optimal structures on source training signal and relay matrices are determined. An iterative and a closed-form power allocation solutions are proposed for both channel estimators. Simulation results show that the proposed schemes outperform the conventional schemes.

Using the finite element analysis model presented in accompanying paper, parametric study was performed in this paper. Various parameters were considered such as the width of wheel loads-induced permanent plastic deformation, backfill, equivalent thickness and orthogonal characteristic of steel mats. The effects of these parameters were analyzed for vertical and rotational displacements, maximum moment and tensile stress. From the parametric studies, it is found that great vertical deflection and tensile stress above allowable flexural tensile strength are developed in steel mats by the wheel loads-induced permanent plastic deformation. Backfill or increasing the thickness of steel mats is a feasible solution on this problem. 요 지 본 논문에서는 전편의 논문에서 제시한 힌지연결부를 갖는 쉘해석모델을 이용하여 변수연구를 수행하였다 . 주요변수에는 중차량 통과에 의하여 발생한 원지반의 영구변형 폭, 되메움, 강재매트의 등가두께 및 강재매트의 이방성 특성이 고려되었다. 이러한 주요변수들이 롤타입강재매트의 수직처짐, 회전변위 및 모멘트와 응력에 미치는 영향을 분석하였다. 분석결과, 차륜하중에 의하여 발생한 동토의 영구소성변형으로 인하여 매우 큰 수직처짐과 허용휨인장강도를 초과하는 인장응력이 발생하는 것으로 나타났다. 이러한 문제는 되메움 또는 강재매트의 등가두께를 증가시킴으로서 쉽게 해결될 수 있다 . Keywords : Permafrost, Steel mat, Parametric analysis, Permanent plastic deformation, backfilling한국토목섬유학회논문집 제13권 4호 2014년 12월 pp. 109 ∼ 117J. Korean Geosynthetics Society Vol.13 No.4 December. 2014 pp. 109 ~ 117DOI: http://dx.doi.org/10.12814/jkgss.2014.13.4.109ISSN:1975-2423(Print) 2287-9528(Online)

Using the finite element analysis model presented in accompanying paper, parametric study was performed in this paper. Various parameters were considered such as the width of wheel loads-induced permanent plastic deformation, backfill, equivalent thickness and orthogonal characteristic of steel mats. The effects of these parameters were analyzed for vertical and rotational displacements, maximum moment and tensile stress. From the parametric studies, it is found that great vertical deflection and tensile stress above allowable flexural tensile strength are developed in steel mats by the wheel loads-induced permanent plastic deformation. Backfill or increasing the thickness of steel mats is a feasible solution on this problem.

The mechanical behavior of frozen soils is different from that of unfrozen soils due to the phase change between water and ice. The strength characteristics of frozen soils are governed by the intrinsic material properties such as grain size, ice and water content, air bubbles, and by externally imposed testing conditions such as temperature, freezing time, and strain rate. Especially, the strength of the frozen soils is generally higher than that of unfrozen soils due to ice binding capacity with soil particles, and is strongly affected by a highly complex interaction between the solid soil skeleton and the pore matrix, composed of ice and unfrozen water. In this study, the direct shear test and unconfined compression test are carried out inside of a large-scaled freezing chamber, and the relationships between cohesion and unconfined compression strength under various freezing temperature conditions are discussed.

The frost depth is one of important factors in the design of structures such as roadways, buried pipeline, and foundations. A frost indicator with methylene blue solution has several advantages with respect to installation cost, maintenance, and simple measurement. However, as a geotechnical engineering aspect, the accuracy of the frost indicator has not been proved yet. This paper presents experimental and field investigations of the accuracy of the frost indicator and contour maps of maximum frost depth. The contour maps of maximum frost depth can be applied to design geo-infrastructure in South Korea.

Frost heave occurs when ground temperature decreases under 0℃ and soil volume expands, which causes roadway and buried pipe line failure due to differential heaving. There are several models to predict volumetric strain caused by frost heave, but they requires expertises who have professional background and experience related to numerical analysis. This study presents an evaluation method to predict volumetric strain caused by frost heave with fundamental physical properties of soils. The evaluation method is assessed with experimental results. 요 지 동결 지반에서 발생하는 동상(frost heave)은 지반의 부등융기를 야기하고, 이때 발생하는 동결하중에 의해 동절기 도로 및 기초 구조물에 피해를 가져온다. 이러한 동결 피해를 방지하기 위해 동상 예측이 필요하다 . 대부분의 동상 예측 방법은 경험과 지식을 갖춘 전문가의 수치해석에 의존하고 있어 현장에서 활용성이 낮다 . 본 논문에서는 동결지반 피해의 주요 원인인 지반의 동상량을 예측하기 위해 기본적인 지반 물성 데이터를 이용해 동상량을 계산할 수 있는 방안을 제시하였으며 , 실내 동상 실험결과와의 비교 분석을 통해 제안된 계산식의 신뢰성을 검토하였다. Keywords : Frost heave, Prediction, Volumetric strain, Evaluation method, Unsaturated soil한국토목섬유학회논문집 제12권 1호 2013년 3월 pp. 93 ∼ 100J. Korean Geosynthetics Society Vol.12 No.1 March. 2013 pp. 93 ~ 100DOI: http://dx.doi.org/10.12814/jkgss.2013.12.1.093

This paper proposes QoS-constrained energy-efficiency (EE) maximization scheme in a multi-antenna wireless powered network. Specifically, considering full CSI at the users, we optimize energy transmit covariance at the power transmitter, the power allocation at the users and the time allocation for energy and information transfer. The EE optimization problem is first converted into its equivalent parameterized subtractive form and, then, the corresponding optimal solution is determined via the Lagrange dual method. The performance of the proposed scheme is validated by simulation.

In this paper, we propose an energy-efficient transmission scheme for wireless powered communication networks with harvest-then-transmit protocol. Specifically, considering fairness among users, we present time resource allocation scheme to maximize the individual energy efficiency(EE) of each user, defined as a ratio of the user throughput to its harvested energy,based on the max-min criterion. EE optimization problem is highly non-convex and difficult to directly tackle. To solve this difficulty, we initially convert two EE problem into its equivalent parameterized subtractive form and, then, the corresponding optimal solution is determined via efficient two-layer iterative algorithm. The simulation results show that the proposed scheme provides better EE performances than those of the conventional schemes and the fairness-based algorithm considerably outperforms the other schemes in terms of the minimum user EE.

Experimental tests have been performed to measure the thermal conductivity of unsaturated soils, and computational models have been widely used to predict thermal conductivity. However, measured values of the thermal conductivity of unsaturated soils cannot be compared with predicted values because of the gradient in moisture content within unsaturated soils. In this study, experimental consolidation tests on saturated unfrozen kaolinite were performed to investigate the effect of dry density and moisture content on thermal conductivity. The results were used to evaluate the validity of a model employed to calculate thermal conductivity.

This paper considers the problem of detecting the pilot contamination attack for multi-antenna secrecy systems. The detection problem is formulated as a binary hypothesis problem and the likelihood ratio or the generalized likelihood ratio is employed as a decision statistic for the detection of the pilot contamination. Using the Neyman-Pearson criterion, we then develop several detection methods under the different assumptions of the channel and noise statistics. To be specific, the cases of interest are as follows: (i) exact knowledge of all covariance matrices, (ii) exact knowledge of the legitimate channel and noise covariance matrices, but no knowledge of the jamming channel covariance matrix and (iii) no knowledge of all covariance matrices. The performance comparison of the proposed schemes with the conventional scheme is performed by simulations.

We propose the source and relay precoder designs to maximize sum rate under individual power constraints in two-way relay system with one relay and multiple sources. However, it is difficult to directly solve the sum rate maximization problem. For this reason, we establish the relationship between sum rate and weighted mean square error(WMSE), and show that the solution of the sum rate maximization problem can be also the solution of the WMSE minimization problem if the weight matrices are properly chosen. Then, based on the relationship between sum rate and WMSE, the sum rate maximization problem is equivalently formulated as the WMSE minimization problem. We finally propose an iterative algorithm for WMSE minimization problem. Simulation results show that the proposed scheme has better sum rate performance than conventional scheme at all SNR regimes.

In this paper, we present a procedure for reliable estimation of the respiration rate using UWB impulse radar. We initially extract the respiratory signal using the energy detector to reduce the effect of the multipath impulse response of the human body. Then, the noise subspace methods are applied to estimate the respiration-rate more accurately. The experimental results show that the proposed method is more reliable than the conventional method.

In this paper, we propose a human detection method in non-stationary clutter environment using ultrawideband (UWB) impulse radar. We treat the foliage swaying in the wind as the non-stationary clutter. It is observed that the signal from the human body is more correlated than the signal from the non-stationary clutter. The method based on the condition number of correlation matrix is used to distinguish the human from the non-stationary clutter. The experimental results show that the proposed method shows better detection probability than the conventional method.

The second scientific Antarctica station of South Korea is under construction at Terra Nova Bay located in east Antarctica. The objective of this study is the evaluation of the frost heave susceptibility of soils sampled from the second station site by performing laboratory frost heaving tests. Experiments are carried out with the soil specimens taken from five different areas at Terra Nova Bay. Test specimens are frozen with constant temperatures at the top and bottom of the specimen at −17 °C and 4 °C, respectively. In addition, grain size analyses and unfrozen water tests are also performed for monitoring the characteristics of the water contained in the permafrost. Frost susceptibility is evaluated by standard methods recommended in UK, US and Japan. Experimental results show that the more the fine contents exist in soils, the more frost heave occurs. The result denotes that grain size has a significant effect on frost heave. The results suggest that the frost heaving susceptibility of the frozen ground at the Antarctic site would be effectively evaluated through the grain size and the frost heaving parameters.