FCFGS-CV-Based Channel Estimation for Wideband MmWave Massive MIMO Systems with Low-Resolution ADCs

In this paper, the fully corrective forward greedy selection-cross validation-based (FCFGS-CV-based) channel estimator is proposed for wideband millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with low-resolution analog-to-digital converters (ADCs). The sparse nature of the mmWave virtual channel in the angular and delay domains is exploited to convert the maximum a posteriori (MAP) channel estimation problem to an optimization problem with a concave objective function and sparsity constraint. The FCFGS algorithm, which is the generalized orthogonal matching pursuit (OMP) algorithm, is used to solve the sparsity-constrained optimization problem. Furthermore, the CV technique is adopted to determine the proper termination condition by detecting overfitting when the sparsity level is unknown.Comment: to appear in IEEE Wireless Communications Letter

Gradient Pursuit-Based Channel Estimation for MmWave Massive MIMO Systems with One-Bit ADCs

In this paper, channel estimation for millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems with one-bit analog-to-digital converters (ADCs) is considered. In the mmWave band, the number of propagation paths is small, which results in sparse virtual channels. To estimate sparse virtual channels based on the maximum a posteriori (MAP) criterion, sparsity-constrained optimization comes into play. In general, optimizing objective functions with sparsity constraints is NP-hard because of their combinatorial complexity. Furthermore, the coarse quantization of one-bit ADCs makes channel estimation a challenging task. In the field of compressed sensing (CS), the gradient support pursuit (GraSP) and gradient hard thresholding pursuit (GraHTP) algorithms were proposed to approximately solve sparsity-constrained optimization problems iteratively by pursuing the gradient of the objective function via hard thresholding. The accuracy guarantee of these algorithms, however, breaks down when the objective function is ill-conditioned, which frequently occurs in the mmWave band. To prevent the breakdown of gradient pursuit-based algorithms, the band maximum selecting (BMS) technique, which is a hard thresholder selecting only the "band maxima," is applied to GraSP and GraHTP to propose the BMSGraSP and BMSGraHTP algorithms in this paper.Comment: to appear in PIMRC 2019, Istanbul, Turke

RESIDUAL STRENGTH OF STRUCTURAL STEELS: SN400, SM520 AND SM570

This paper presents post-fire mechanical properties of mild to high-strength steels commonly used in building structures in Korea. Steel is one of the main materials for building construction due to fast construction, light weight, and high seismic resistance. However, steel usually loses its strength and stiffness at elevated temperatures, especially over 600°C. But steel can regain some of its original mechanical properties after cooling down from the fire. Therefore, it is important to accurately evaluate the reliable performance of steel to reuse or repair the structures. For this reason, an experimental study was performed to examine the post-fire mechanical properties of steel plates SN400, SM520 and SM570 after cooling down from elevated temperatures up to 900°C. The post-fire stress-strain curves, elastic modulus, yield and ultimate strengths and residual factors were obtained and discussed

Dominant Channel Estimation via MIPS for Large-Scale Antenna Systems with One-Bit ADCs

In large-scale antenna systems, using one-bit analog-to-digital converters (ADCs) has recently become important since they offer significant reductions in both power and cost. However, in contrast to high-resolution ADCs, the coarse quantization of one-bit ADCs results in an irreversible loss of information. In the context of channel estimation, studies have been developed extensively to combat the performance loss incurred by one-bit ADCs. Furthermore, in the field of array signal processing, direction-of-arrival (DOA) estimation combined with one-bit ADCs has gained growing interests recently to minimize the estimation error. In this paper, a channel estimator is proposed for one-bit ADCs where the channels are characterized by their angular geometries, e.g., uniform linear arrays (ULAs). The goal is to estimate the dominant channel among multiple paths. The proposed channel estimator first finds the DOA estimate using the maximum inner product search (MIPS). Then, the channel fading coefficient is estimated using the concavity of the log-likelihood function. The limit inherent in one-bit ADCs is also investigated, which results from the loss of magnitude information.Comment: to appear in GLOBECOM 2018, Abu Dhabi, UA

Meta-Heuristic Fronthaul Bit Allocation for Cell-free Massive MIMO Systems

Limited capacity of fronthaul links in a cell-free massive multiple-input multiple-output (MIMO) system can cause quantization errors at a central processing unit (CPU) during data transmission, complicating the centralized rate optimization problem. Addressing this challenge, we propose a harmony search (HS)-based algorithm that renders the combinatorial non-convex problem tractable. One of the distinctive features of our algorithm is its hierarchical structure: it first allocates resources at the access point (AP) level and subsequently optimizes for user equipment (UE), ensuring a more efficient and structured approach to resource allocation. Our proposed algorithm deals with rigorous conditions, such as asymmetric fronthaul bit allocation and distinct quantization error levels at each AP, which were not considered in previous works. We derive a closed-form expression of signal-to-interference-plusnoise ratio (SINR), in which additive quantization noise model (AQNM) based distortion error is taken into account, to define the mathematical expression of spectral efficiency (SE) for each UE. Also, we provide analyses on computational complexity and convergence to investigate the practicality of proposed algorithm. By leveraging various performance metrics such as total SE and max-min fairness, we demonstrate that the proposed algorithm can adaptively optimize the fronthaul bit allocation depending on system requirements. Finally, simulation results show that the proposed algorithm can achieve satisfactory performance while maintaining low computational complexity, as compared to the exhaustive search methodComment: 16 pages, 13 figures, accepted to IEEE Transactions on Wireless Communications (TWC

Human Brain Astrocytes Mediate TRAIL-mediated Apoptosis after Treatment with IFN-γ

TNF-related apoptosis inducing ligand (TRAIL) expressions were studied in primary human brain astrocytes in response to pro-inflammatory cytokines. When astrocytes were treated with IL-1β, TNF-α or IFN-γ, TRAIL was induced in cultured fetal astrocytes. In particular, IFN-γ induced the highest levels of TRAIL in cultured astrocytes. When astrocytes were prereated with IFN-γ, they induced apoptosis in TRAIL-sensitive Peer cells. Our results suggest that IFN-γ modulates the expression of TRAIL in astrocytes, which may enhance cytotoxic sensitivity of infiltrating immune cells or brain cells other than astrocytes during inflammation of brain

Channel Estimation via Gradient Pursuit for MmWave Massive MIMO Systems with One-Bit ADCs

In millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, one-bit analog-to-digital converters (ADCs) are employed to reduce the impractically high power consumption, which is incurred by the wide bandwidth and large arrays. In practice, the mmWave band consists of a small number of paths, thereby rendering sparse virtual channels. Then, the resulting maximum a posteriori (MAP) channel estimation problem is a sparsity-constrained optimization problem, which is NP-hard to solve. In this paper, iterative approximate MAP channel estimators for mmWave massive MIMO systems with one-bit ADCs are proposed, which are based on the gradient support pursuit (GraSP) and gradient hard thresholding pursuit (GraHTP) algorithms. The GraSP and GraHTP algorithms iteratively pursue the gradient of the objective function to approximately optimize convex objective functions with sparsity constraints, which are the generalizations of the compressive sampling matching pursuit (CoSaMP) and hard thresholding pursuit (HTP) algorithms, respectively, in compressive sensing (CS). However, the performance of the GraSP and GraHTP algorithms is not guaranteed when the objective function is ill-conditioned, which may be incurred by the highly coherent sensing matrix. In this paper, the band maximum selecting (BMS) hard thresholding technique is proposed to modify the GraSP and GraHTP algorithms, namely the BMSGraSP and BMSGraHTP algorithms, respectively. The BMSGraSP and BMSGraHTP algorithms pursue the gradient of the objective function based on the band maximum criterion instead of the naive hard thresholding. In addition, a fast Fourier transform-based (FFT-based) fast implementation is developed to reduce the complexity. The BMSGraSP and BMSGraHTP algorithms are shown to be both accurate and efficient, whose performance is verified through extensive simulations.Comment: to appear in EURASIP Journal on Wireless Communications and Networkin

Crack-Resistance Behavior of an Encapsulated, Healing Agent Embedded Buffer Layer on Self-Healing Thermal Barrier Coatings

In this work, a novel thermal barrier coating (TBC) system is proposed that embeds silicon particles in coating as a crack-healing agent. The healing agent is encapsulated to avoid unintended reactions and premature oxidation. Thermal durability of the developed TBCs is evaluated through cyclic thermal fatigue and jet engine thermal shock tests. Moreover, artificial cracks are introduced into the buffer layer’s cross section using a microhardness indentation method. Then, the indented TBC specimens are subject to heat treatment to investigate their crack-resisting behavior in detail. The TBC specimens with the embedded healing agents exhibit a relatively better thermal fatigue resistance than the conventional TBCs. The encapsulated healing agent protects rapid large crack openings under thermal shock conditions. Different crack-resisting behaviors and mechanisms are proposed depending on the embedding healing agents

Crack-Growth Behavior in Thermal Barrier Coatings with Cyclic Thermal Exposure

Crack-growth behavior in yttria-stabilized zirconia-based thermal barrier coatings (TBCs) is investigated through a cyclic thermal fatigue (CTF) test to understand TBCs’ failure mechanisms. Initial cracks were introduced on the coatings’ top surface and cross section using the micro-indentation technique. The results show that crack length in the surface-cracked TBCs grew parabolically with the number of cycles in the CTF test. Failure in the surface-cracked TBC was dependent on the initial crack length formed with different loading levels, suggesting the existence of a threshold surface crack length. For the cross section, the horizontal crack length increased in a similar manner as observed in the surface. By contrast, in the vertical direction, the crack did not grow very much with CTF testing. An analytical model is proposed to explain the experimentally-observed crack-growth behavior