REV Journal on Electronics and Communications
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On The Performance Of 1-Bit ADC In Massive MIMO Communication Systems
Get PDFMassive multiple-input multiple-output (MIMO) with low-resolution analog-to-digital converters is a rational solution to deal with hardware costs and accomplish optimal energy efficiency. In particular, utilizing 1-bit ADCs is one of the best choices for massive MIMO systems. This paper investigates the performance of the 1-bit ADC in the wireless coded communication systems where the robust channel coding, protograph low-density parity-check code (LDPC), is employed. The investigation reveals that the performance of the conventional 1-bit ADC with the truncation limit of 3-sigma is severely destroyed by the quantization distortion even when the number of antennas increases to 100. The optimized 1-bit ADC, though having substantial performance gain over the conventional one, is also affected by the quantization distortion at high coding rates and low MIMO configurations. Importantly, the investigation results suggest that the protograph LDPC codes should be re-designed to combat the negative effect of the quantization distortion of the 1-bit ADC
Integrated On-Silicon and On-glass Antennas for Mm-Wave Applications
Get PDFThe paper presents several integrated high frequency antenna prototypes based on Si/CMOS and on-glass technologies for millimeter-wave (mm-wave) applications. On-chip loop antenna and dipole radiator are presented. In addition, a wide-band dipole-patch antenna design for the range of 74 – 104 GHz is integrated into a CMOS chip with an on-chip pulse generator. In addition, an implementation of a fully on-Silicon antenna array integrated with a timed-array transmitter. To control the beam-forming of this array, a digital-based time adjustment circuit is integrated together with the antenna array. Simulated and measured data including return loss, and radiation patterns are presented. This paper also introduces an on-glass antenna prototypes fabricated on quartz substrate. The on-glass antenna is to demonstrate for handset or automobile’s windshield/windows applications where radio waves could be transmitted and received from various directions. The results show several compact antenna candidates integrated by both Silicon and quartz substrates towards mm-Wave/sub-mm-Wave sensing and communication applications
Combining Content and Social Features in a Deep Learning Approach to Vietnamese Email Prioritization
Get PDFThe email overload problem has been discussed in numerous email-related studies. One of the possible solutions to this problem is email prioritization, which is the act of automatically predicting the importance levels of received emails and sorting the user’s inbox accordingly. Several learning-based methods have been proposed to address the email prioritization problem using content features as well as social features. Although these methods have laid the foundation works in this field of study, the reported performance is far from being practical. Recent works on deep neural networks have achieved good results in various tasks. In this paper, the authors propose a novel email prioritization model which incorporates several deep learning techniques and uses a combination of both content features and social features from email data. This method targets Vietnamese emails and is tested against a self-built Vietnamese email corpus. Conducted experiments explored the effects of different model configurations and compared the effectiveness of the new method to that of a previous work
Evaluating the effect of self-interference on the performance of full-duplex two-way relaying communication with energy harvesting
Get PDFIn this paper, we study the throughput and outage probability (OP) of two-way relaying (TWR) communication system with energy harvesting (EH). The system model consists two source nodes and a relay node which operates in full-duplex (FD) mode. The effect of self-interference (SI) due to the FD operation on the system performance is evaluated for both one-way full duplex (OWFD) and two-way full duplex (TWFD) diagrams where the amplify-and-forward (AF) relay node collects energy harvesting with the time switching (TS) scheme. We first propose an individual OP expression for each specific source. Then, we derive the exact closed-form overall OP expression for the OWFD diagram. For the TWFD diagram, we propose an approximate closed-form expression for the overall OP. The overall OP comparison among hybrid systems (Two-Way Half-Duplex (TWHD), OWFD, TWFD) are also discussed. Finally, the numerical/simulated results are presented for Rayleigh fading channels to demonstrate the correction of the proposed analysis
An Improving Way For Website Security Assessment
Get PDFNowadays, the Internet plays a crucial role in our society. AmongInternet services, web-based services are very popular thatbecome the target of security attacks. Hence, securing websitesand connection to the users is important. If we own or manage awebsite, we certainly concern about how secure it is. Forassessing the security level of a website, we usually take someaction, including testing the website using security scanningtools. Unfortunately, most of scanning tools have limitations andneed to be updated frequently for new vulnerabilities. Using onlyone scanning tool is sometime not enough to determine securitylevel of a website. In this paper we propose a frameworksupporting website security assessment. The idea of thisframework is to integrate different scanning tools into theframework. We then write a program to implement thisframework with a real website. We guide the users how to add anew scanning tool to this framework, manage it and generate afinal report
Improving TDWZ Correlation Noise Estimation: A Deep Learning based Approach
Get PDFTransform domain Wyner-Ziv video coding (TDWZ) has shown its benefits in compressing video applications with limited resources such as visual surveillance systems, remote sensing and wireless sensor networks. In TDWZ, the correlation noise model (CNM) plays a vital role since it directly affects to the number of bits needed to send from the encoder and thus the overall TDWZ compression performance. To achieve CNM with high accurate for TDWZ, we propose in this paper a novel CNM estimation approach in which the CNM with Laplacian distribution is adaptively estimated based on a deep learning (DL) mechanism. The proposed DL based CNM includes two hidden layers and a linear activation function to adaptively update the Laplacian parameter. Experimental results showed that the proposed TDWZ codec significantly outperforms the relevant benchmarks, notably by around 35% bitrate saving when compared to the DISCOVER codec and around 22% bitrate saving when compared to the HEVC Intra benchmark while providing a similar perceptual quality
Low-Dose CT Image Denoising using Image Decomposition and Sparse Representation
Get PDFX-ray computed tomography (CT) is now a widely used imaging modality for numerous medical purposes. The risk of high X-ray radiation may induce genetic, cancerous and other diseases, demanding the development of new image processing methods that are able to enhance the quality of low-dose CT images. However, lowering the radiation dose increases the noise in acquired images and hence affects important diagnostic information. This paper contributes an efficient denoising method for low-dose CT images. A noisy image is decomposed into three component images of low, medium and high frequency bands; noise is mainly presented in the medium and high component images. Then, by exploiting the fact that a small image patch of the noisy image can be approximated by a linear combination of several elements in a given dictionary of noise-free image patches generated from noise-free images taken at nearly the same position with the noisy image, noise in these medium and high component images are effectively eliminated.Specifically, we give new solutions for image decomposition to easily control the filter parameters, for dictionary construction to improve the effectiveness and reduce the running-time. Instead of using a large dataset of patches, only a structured small part of patches extracted from the raw data is used to form a dictionary, to be used in sparse coding. In addition, we illustrate the effectiveness of the proposed method in preserving image details which are subtle but clinically important. Experimental results conducted on both synthetic and real noise data demonstrate that the proposed method is competitive with the state-of-the-art methods
