Ergodic Achievable Rate Maximization of RIS-assisted Millimeter-Wave MIMO-OFDM Communication Systems

Reconfigurable intelligent surface (RIS) has attracted extensive attention in recent years. However, most research focuses on the scenario of the narrowband and/or instantaneous channel state information (CSI), while wide bandwidth with the use of millimeter-wave (mmWave) (including sub-Terahertz) spectrum is a major trend in next-generation wireless communications, and statistical CSI is more practical to obtain in realistic systems. Thus, we {consider} the ergodic achievable rate of RIS-assisted mmWave multiple-input multiple-output orthogonal frequency division multiplexing communication systems. The widely used Saleh-Valenzuela channel model is adopted to characterize the mmWave channels and only the statistical CSI is available. We first derive the approximations of the ergodic achievable rate by means of the majorization theory and Jensen's inequality. Then, an alternating optimization based algorithm is proposed to maximize the ergodic achievable rate by jointly designing the transmit covariance matrix at the base station and the reflection coefficients at the RIS. Specifically, the design of the transmit covariance matrix is transformed into a power allocation problem and solved by spatial-frequency water-filling. The reflection coefficients are optimized by the Riemannian conjugate gradient algorithm. Simulation results corroborate the effectiveness of the proposed algorithms.Comment: submitted for possible publication. in IEEE Transactions on Wireless Communications, 202

Ergodic Achievable Rate Analysis and Optimization of RIS-assisted Millimeter-Wave MIMO Communication Systems

Reconfigurable intelligent surfaces (RISs) have emerged as a prospective technology for next-generation wireless networks due to their potential in coverage and capacity enhancement. Previous works on achievable rate analysis of RIS-assisted communication systems have mainly focused on the rich-scattering environment where Rayleigh and Rician channel models can be applied. This work studies the ergodic achievable rate of RIS-assisted multiple-input multiple-output communication systems in millimeter-wave band with limited scattering under the Saleh-Valenzuela channel model. Firstly, we derive an upper bound of the ergodic achievable rate by means of majorization theory and Jensen's inequality. The upper bound shows that the ergodic achievable rate increases logarithmically with the number of antennas at the base station (BS) and user, the number of the reflection units at the RIS, and the eigenvalues of the steering matrices associated with the BS, user and RIS. Then, we aim to maximize the ergodic achievable rate by jointly optimizing the transmit covariance matrix at the BS and the reflection coefficients at the RIS. Specifically, the transmit covariance matrix is optimized by the water-filling algorithm and the reflection coefficients are optimized using the Riemannian conjugate gradient algorithm. Simulation results validate the effectiveness of the proposed optimization algorithms.Comment: 30 pages, 11 figure

How to Differentiate between Near Field and Far Field: Revisiting the Rayleigh Distance

Future wireless communication systems are likely to adopt extremely large aperture arrays and millimeter-wave/sub-THz frequency bands to achieve higher throughput, lower latency, and higher energy efficiency. Conventional wireless systems predominantly operate in the far field (FF) of the radiation source of signals. As the array size increases and the carrier wavelength shrinks, however, the near field (NF) becomes non-negligible. Since the NF and FF differ in many aspects, it is essential to distinguish their corresponding regions. In this article, we first provide a comprehensive overview of the existing NF-FF boundaries, then introduce a novel NF-FF demarcation method based on effective degrees of freedom (EDoF) of the channel. Since EDoF is intimately related to spectral efficiency, the EDoF-based border is able to characterize key channel performance more accurately, as compared with the classic Rayleigh distance. Furthermore, we analyze the main features of the EDoF-based NF-FF boundary and provide insights into wireless system design

Structure-based Functional Analysis Reveals a Role for the SM Protein Sly1p in Retrograde Transport to the Endoplasmic Reticulum

Sec1p/Munc18 (SM) proteins are essential for membrane fusion events in eukaryotic cells. Here we describe a systematic, structure-based mutational analysis of the yeast SM protein Sly1p, which was previously shown to function in anterograde endoplasmic reticulum (ER)-to-Golgi and intra-Golgi protein transport. Five new temperature-sensitive (ts) mutants, each carrying a single amino acid substitution in Sly1p, were identified. Unexpectedly, not all of the ts mutants exhibited striking anterograde ER-to-Golgi transport defects. For example, in cells of the novel sly1-5 mutant, transport of newly synthesized lysosomal and secreted proteins was still efficient, but the ER-resident Kar2p/BiP was missorted to the outside of the cell, and two proteins, Sed5p and Rer1p, which normally shuttle between the Golgi and the ER, failed to relocate to the ER. We also discovered that in vivo, Sly1p was associated with a SNARE complex formed on the ER, and that in vitro, the SM protein directly interacted with the ER-localized nonsyntaxin SNAREs Use1p/Slt1p and Sec20p. Furthermore, several conditional mutants defective in Golgi-to-ER transport were synthetically lethal with sly1-5. Together, these results indicate a previously unrecognized function of Sly1p in retrograde transport to the endoplasmic reticulum

ConvLSTM-Att: An Attention-Based Composite Deep Neural Network for Tool Wear Prediction

In order to improve the accuracy of tool wear prediction, an attention-based composite neural network, referred to as the ConvLSTM-Att model (1DCNN-LSTM-Attention), is proposed. Firstly, local multidimensional feature vectors are extracted with the help of a one-dimensional convolutional neural network (1D-CNN), which avoids the loss of wear features caused by manual feature extraction. Then the temporal relationship learning between multidimensional feature vectors is performed by introducing a long short-term memory (LSTM) network to make up for the lack of long-short distance dependence of the captured sequence of the CNN network. Finally, an attention mechanism is applied to strengthen the ability to extract key information from tool-wearing temporal features. The proposed ConvLSTM-Att model is trained with the measured tool wear data and then performs as a tool wear predictor. The model is compared with several state-of-the-art models on the PHM tool wear data sets. It significantly outperforms the other models in terms of prediction accuracy, but with similar computational complexity

Internal herniation through lesser omentum hiatus and gastrocolic ligament with malrotation: a case report

Abstract Background Internal herniation through lesser omentum hiatus and gastrocolic ligament with malrotation is extremely rare. This type of internal hernia has rarely been described before. Preoperative diagnosis is difficult and prone to misdiagnosis. Case presentation A 38-year-old Chinese woman was an emergency admission to our hospital with a sudden onset of acute epigastralgia for the past 14 hours. We made a presumptive diagnosis of gastrointestinal perforation and septic shock. Due to the acute onset and rapid progress, she received timely surgical treatment. During operation, we observed that her small intestine herniated into the hepatogastric ligament and ligamentum gastrocolicum hiatus accompanied with intestinal malrotation that resulted in internal hernia. We found a diverticulum of approximately 3.0 × 6.0 cm sited at a distance of 80 cm from the ileocecal intestine. We resected the strangulated intestinal loop and the diverticulum, performed an appendicectomy, and closed the ligamentous fissure. Postoperation, she recovered smoothly, without any complications, and was discharged on day 6. Conclusions A case of internal hernia formation is quite rare; accurate preoperative diagnosis and timely surgery are essential because it can cause strangulation of the ileus. However, the incidence of this internal herniation is low and preoperative diagnosis is difficult. An accurate preoperative diagnosis of internal hernia is still a challenge

Investigational Study of Mesenchymal Stem Cells on Lung Cancer Cell Proliferation and Invasion

Background and objective Mesenchymal stem cells (MSC) are adult stem cells derived from mesoderm. Evidence has shown that MSC could migrate towards tumor tissue and differentiate into tumor associated fibroblast in tumor microenvironment, which influences tumor growth and metastasis. However, the reports of MSC in non-small cell lung cancer (NSCLC) are few and controversial. The aim of this study is to explore the chemotaxis of MSC towards NSCLC and to test the effects of MSC on the proliferation and invasion ability of NSCLC. Methods Transwell assay was used to test MSC and NSCLC migration and invasion, and Thymidine incorporation assay was adopted to measure NSCLC cells proliferation. The expression of interleukin-6 (IL-6), insulinlike growth factor (IGF-1), vascular endothelial growth factor (VEGF) and dickkopf-related protein 1 (DKK1) of MSCs were determined by real time PCR. A549 lung cancer xenograft animal tumor model was set up to evaluate the MSC effect in vivo. Results Lung cancer cells could attract MSC tropism. MSC conditioned medium favored lung cancer cell proliferation and lung cancer cells stimulated the expression of IL-6, IGF-1, VEGF and DKK1 on MSCs. In vivo animal study showed that the tumor with MSC injection grew much faster compared to control group. Conclusion MSCs could migrate towards NSCLC cells and favor tumor growth. In turn, NSCLC cells could stimulate the overexpression of cytokines on MSCs which are essential for the tumor growth