This paper considers channel estimation and system performance for the uplink of a single-cell massive multiple-input multiple-output (MIMO) system. Each receive antenna of the base station (BS) is assumed to be equipped with a pair of onebit analog-to-digital converters (ADCs) to quantize the real and imaginary part of the received signal. We first propose an approach for channel estimation that is applicable for both flat and frequency-selective fading, based on the Bussgang decomposition that reformulates the nonlinear quantizer as a linear function with identical first-and second-order statistics. The resulting channel estimator outperforms previously proposed approaches across all SNRs. We then derive closed-form expressions for the achievable rate in flat fading channels assuming low SNR and a large number of users for the maximal ratio and zero forcing receivers that takes channel estimation error due to both noise and one-bit quantization into account. The closed-form expressions in turn allow us to obtain insight into important system design issues such as optimal resource allocation, maximal sum spectral efficiency, overall energy efficiency, and number of antennas. Numerical results are presented to verify our analytical results and demonstrate the benefit of optimizing system performance accordingly.

A new Co(II)-based MOF, {[Co(tzpa)(OH)(HO)]·DMF} (1) (Htzpa = 5-(4-(tetrazol-5-yl)phenyl)isophthalic acid), was constructed by employing a tetrazolyl-carboxyl ligand Htzpa. 1 possesses 1D tubular channels that are decorated by μ-OH groups, uncoordinated carboxylate O atoms, and open metal centers generated by the removal of coordinated water molecules, leading to high CO adsorption capacity and significantly selective capture for CO over CH and CO in the temperature range of 298-333 K. Moreover, 1 shows the chemical stability in acidic and basic aqueous solutions. Grand canonical Monte Carlo simulations identified multiple CO-philic sites in 1. In addition, the activated 1 as the heterogeneous Lewis and Brønsted acid bifunctional catalyst facilitates the chemical fixation of CO coupling with epoxides into cyclic carbonates under ambient conditions.

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Seven new isostructural lanthanide metal-organic frameworks (Ln-MOFs), [Ln(Hpzbc)2(NO3)]·H2O (1-Ln, Ln = Nd(3+), Sm(3+), Eu(3+), Gd(3+), Tb(3+), Er(3+), and Yb(3+) ions, H2pzbc = 3-(1H-pyrazol-3-yl) benzoic acid), with one-dimensional (1D) channels decorated by nitrate anions and pyrazoyl groups have been constructed. 1-Ln, as revealed by structural analysis, represent uncommon microporous 3D Ln-pyrazoyl-carboxyl systems using pyrazoyl-carboxyl bifunctional ligands as bridges. The luminescent investigations show that 1-Eu is an excellent MOF-based fluorescent probe, with high sensitivity, selectivity, and simple regeneration, for environmentally relevant Fe(3+) and Cr2O7(2-) ions. 1-Eu also presents highly selective capture for CO2 over N2 and CH4 due to the multiple binding sites for CO2 molecules, which were supported by Grand Canonical Monte Carlo (GCMC) simulations.

The first strontium-based MOF possessing polar tubular channels embedded with a high density of open Lewis acidic metal sites and basic oxalamide groups was constructed, which shows not only a high CO and CH adsorption capability and significant selectivity for CO over both CH and CO, and for CH over CH, but also size-selective chemical conversion of CO with epoxides producing cyclic carbonates under ambient conditions.

Abstract-In this letter, we investigate the downlink performance of massive multiple-input multiple-output (MIMO) systems where the base station is equipped with one-bit analogto-digital/digital-to-analog converters (ADC/DACs). Considering training-based transmission, we assume the base station (BS) employs the linear minimum mean-squared-error (LMMSE) channel estimator and treats the channel estimate as the true channel to precode the data symbols. We derive an expression for the downlink achievable rate for matched-filter (MF) precoding. A detailed analysis of the resulting power efficiency is pursued using our expression of the achievable rate. Numerical results are presented to verify our analysis. In particular it is shown that, compared with conventional massive MIMO systems, the performance loss in one-bit massive MIMO systems can be compensated for by deploying approximately 2.5 times more antennas at the BS.

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Steganography represents the art of unobtrusively concealing a secrete message within some cover data. The key scope of this work is about visual steganography techniques that hide a full-sized color image / video within another. A majority of existing works are devoted to the image case, where both secret and cover data are images. We empirically validate that image steganography model does not naturally extend to the video case (i.e., hiding a video into another video), mainly because it completely ignores the temporal redundancy within consecutive video frames. Our work proposes a novel solution to the problem of video steganography. The technical contributions are two-fold: first, the residual between two consecutive frames tends to zero at most pixels. Hiding such highly-sparse data is significantly easier than hiding the original frames. Motivated by this fact, we propose to explicitly consider inter-frame residuals rather than blindly applying image steganography model on every video frame. Specifically, our model contains two branches, one of which is specially designed for hiding inter-frame difference into a cover video frame and the other instead hides the original secret frame. A simple thresholding method determines which branch a secret video frame shall choose. When revealing the concealed secret video, two decoders are devised, revealing difference or frame respectively. Second, we develop the model based on deep convolutional neural networks, which is the first of its kind in the literature of video steganography. In experiments, comprehensive evaluations are conducted to compare our model with both classic least significant bit (LSB) method and pure image steganography models. All results strongly suggest that the proposed model enjoys advantages over previous methods. We also carefully investigate key factors in the success of our deep video steganography model. The first two authors contribute equally. Yadong Mu is the corresponding author of this work. cover secret Alice container Eve Bob decoded secret contain secret message? Figure 1: The full scheme of steganography. See main text for more explanation.