2020 37th National Radio Science Conference (NRSC)最新文献

Adaptive Femtocell Accessing Control in A 5g Heterogeneous Network 5g异构网络中的自适应Femtocell接入控制

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235120

M. M. Mohamed, H. El-Badawy, Reem Abdelhadi, A. Ammar

{"title":"Adaptive Femtocell Accessing Control in A 5g Heterogeneous Network","authors":"M. M. Mohamed, H. El-Badawy, Reem Abdelhadi, A. Ammar","doi":"10.1109/NRSC49500.2020.9235120","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235120","url":null,"abstract":"Heterogeneous network is considered a powerful key to increase network capacity and provide high quality of service (QoS) for network users. However, in a heterogeneous network composed of femtocells and a macrocell, Macro users in poor signal places prefer to access to the nearest femtocell. Thus, these accessing will have a bad effect on femto users. Therefore, in this paper, first we propose an adaptive femtocell access system model to control the resource allocation between femto users (FUs) and macro users (MUs). Using the proposed adaptive system model, the most appropriate femtocell access mode will be determined. Second, a borrowing technique is proposed to be an arm of safety for femtocells that suffer from high traffic density. Simulation results show the adaptation of femtocell access modes with a varying network density to guarantee high QoS for FUs and help suffered MUs to get services without affecting the demands of FUs. Also; Simulation results show that the overall network performance can be improved using the proposed borrowing technique model as the number of blocking MUs can be decreased from 93 MU to zero MU. Also results show that, the proposed model will outperform the system performance by 52% with respect to the closed system model.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"17 1","pages":"85-94"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73095219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Application of Artificial Neural Networks to the Automation of Bandgap Reference Synthesis 人工神经网络在带隙参考综合自动化中的应用

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235111

Nabil R. Soliman, Karim D. Khalil, Ahmed M. Abd El Khalik, H. Omran

{"title":"Application of Artificial Neural Networks to the Automation of Bandgap Reference Synthesis","authors":"Nabil R. Soliman, Karim D. Khalil, Ahmed M. Abd El Khalik, H. Omran","doi":"10.1109/NRSC49500.2020.9235111","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235111","url":null,"abstract":"Bandgap voltage references are present in virtually every analog/mixed-signal system. However, their design still remains a time-consuming procedure that requires extensive designer expertise and validation. In this paper, an automated bandgap synthesis procedure is used to generate a dataset that maps the specifications of the synthesized bandgap reference circuit to their corresponding designer's degrees of freedom. This dataset is then used to train a neural network to predict the choice of the degrees of freedom in order to meet arbitrary circuit specifications specified by the user including variations due to design corners and random mismatch. The automated bandgap synthesis procedure uses precomputed look-up tables rather than invoking a circuit simulator in the loop, which enables generating a large dataset of training examples in short time. The choice of the degrees of freedom predicted by the neural network is then re-fed to the bandgap synthesis procedure to verify the accuracy of the prediction and obtain the complete solution of the synthesized circuit. The results demonstrate that the trained neural network is capable of making successful predictions of good accuracy in a wide multi-dimensional design space.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"5 1","pages":"106-116"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89105782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Channel Matched Sparse Non-Orthogonal frequency division multiplexing (CM-SNOFDM) Operating in Underwater Acoustic Channels 信道匹配稀疏非正交频分复用(CM-SNOFDM)在水声信道中的应用

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235108

S. El-Khamy, Dalia I. Mohamed

引用次数: 1

Angular Displacement Sensor Based on Planar Circular Split Ring Resonator 基于平面圆裂环谐振器的角位移传感器

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235102

E. A. El-Refaay, S. Zainud-Deen, H. Malhat

引用次数: 2

Meander Dipole Antenna for Low Frequency Applications 用于低频应用的弯曲偶极天线

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235109

M. Ismail, A. R. Eldamak, H. Ghali

引用次数: 0

Reliability Analysis Model of the Digital Reactor Protection System 数字电抗器保护系统可靠性分析模型

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235117

Amany S. Saber, M. Shaat, A. El-Sayed, Hanaa Torkey, M. Shouman

引用次数: 1

Single Image Super Resolution Using Discrete Cosine Transform Driven Regression Tree 单图像超分辨率使用离散余弦变换驱动的回归树

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235100

Y. Badran, G. Salama, T. Mahmoud, Aiman M. Mousa, Adel E. Moussa

{"title":"Single Image Super Resolution Using Discrete Cosine Transform Driven Regression Tree","authors":"Y. Badran, G. Salama, T. Mahmoud, Aiman M. Mousa, Adel E. Moussa","doi":"10.1109/NRSC49500.2020.9235100","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235100","url":null,"abstract":"Single image super resolution restoration is a process for solving the ill-posed problem of achieving a high resolution image from one low resolution image. This process is considered an active point of research due to the increased demands for high resolution imagery in many applications. This paper presents a proposed methodology for single image super resolution based on replacing the traditional discrete cosine transform basis. These bases are replaced by learned filters that can transfer the low resolution image from the spatial domain to high resolution coefficients in the discrete cosine domain. Accordingly, these estimated filters can then be applied to produce a high resolution image in the spatial domain through the standard inverse discrete cosine transform process. To learn these transformation filters two modifications in the decision tree algorithm are introduced to adapt the tree performance for the super resolution task. This is performed such that the node splitting decision depends on external features that minimize the regression errors. Experimental results demonstrate that the performance of the proposed algorithm is superior to that of the traditional interpolation single image super resolution method.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"55 7","pages":"128-136"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91466050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optical Cavity with Large Operational Bandwidth using Silicon-Based Slotted Micromirrors 基于硅基开槽微镜的大工作带宽光腔

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235103

M. Abdallah, Y. Sabry, A. Mahfouz, F. Marty, T. Bourouina, H. Omran

{"title":"Optical Cavity with Large Operational Bandwidth using Silicon-Based Slotted Micromirrors","authors":"M. Abdallah, Y. Sabry, A. Mahfouz, F. Marty, T. Bourouina, H. Omran","doi":"10.1109/NRSC49500.2020.9235103","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235103","url":null,"abstract":"In this paper, we report FDTD simulations and experimental results of novel silicon-based optical microcavity comprising of two slotted micromirrors. While the normal range for silicon microcavities is limited by its absorption below 1.1 μm, we demonstrate a silicon cavity that is capable of operation from the visible spectrum till the telecom C-band. Deep reactive ion etching (DRIE) is used to fabricate the deeply etched microcavity mirrors. The structure is metallized with gold to enhance mirrors’ reflectivity. The slotted mirror and the cavity structure are simulated using finite difference time domain (FDTD), and the results are reported showing a quality factor of 2796 for visible TM excitation and a quality factor of 2346 for NIR TM excitation. The experimental results report the characteristics of the resonator and verify its operation in the NIR and visible ranges. The measured quality factor (Q) is 2067 around the 565 nm peak and 1922 around the 1550 nm peak. Such a microcavity would present a major step towards realizing visible laser on silicon for micro optofluidic applications.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"24 1","pages":"222-229"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89410538","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

An Energy Efficient Constraint RRH to Bbu Association in Cloud Radio Access Networks 云无线接入网中能效约束RRH - Bbu关联

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235119

H. Hesham, M. Ashour, T. el-Shabrawy

{"title":"An Energy Efficient Constraint RRH to Bbu Association in Cloud Radio Access Networks","authors":"H. Hesham, M. Ashour, T. el-Shabrawy","doi":"10.1109/NRSC49500.2020.9235119","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235119","url":null,"abstract":"With the evolution of 5G and the motivation to provide high demand rates to users anywhere anytime, Cloud Radio Access Network (C-RAN) has become one of the most attractive research fields in the development of wireless communication. Alongside the many benefits of C-RAN including cost-effectiveness, dynamic resource allocation, and high rate provisioning comes the challenge of how to allocate the resources and optimize the energy utilization in the centralized cloud. This paper formulates an energy efficient constraint Base Band Unit to Remote Radio Head association according to user rate demands through minimizing the power consumption by deactivating Base Band Units in the Data Center. The formulation is dependent on both the processing capability of the servers in the cloud, and the user rate requirement. These two attributes introduce a challenge when allocating resources in a C-RAN system. Dual constraint bin packing approach is proposed to solve the energy problem. Results were tested with a varying user load showing a drop in the power consumption in the Data Center while successfully maintaining the total rate requirement of the system with a given bandwidth allocation based on Base Band Unit to Base Band Unit interference and frame processing deadline.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"3 1","pages":"155-163"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87030559","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Prediction of Epileptic Seizures: A Statistical Approach with DCT Compression 预测癫痫发作:DCT压缩的统计方法

2020 37th National Radio Science Conference (NRSC) Pub Date : 2020-09-08 DOI: 10.1109/NRSC49500.2020.9235107

Nancy El-Fequi, A. Ashour, Entessar Saaed Gemeaa, F. A. Abd El-Samie

{"title":"Prediction of Epileptic Seizures: A Statistical Approach with DCT Compression","authors":"Nancy El-Fequi, A. Ashour, Entessar Saaed Gemeaa, F. A. Abd El-Samie","doi":"10.1109/NRSC49500.2020.9235107","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235107","url":null,"abstract":"Electroencephalogram (EEG) signal compression is an essential process to speed-up the medical signal transmission with reduced storage requirements, costs, and required bandwidth. The main objective of the present work is to compress the EEG signals and study the effect of the compression process on the epileptic seizure prediction. A lossy EEG data compression scheme using Discrete Cosine Transform (DCT) is applied, followed by seizure prediction. The used dataset includes healthy, pre-ictal, and ictal signals with multiple channels. The EEG signals are segmented to segments of 10 sec length. Also, the probability density functions (PDFs) for seizure prediction are measured, including amplitude, derivative, local media, local variance, and local mean PDFs. During the testing phase, only the selected bins of PDFs are used in the prediction process to identify each signal segment as pre-ictal or normal. A method of equal benefit decision fusion is carried out in the final prediction stage leading to a single sequence of decisions representing the activities of all segments. Relative to a patient-specific estimation level, this series after being filtered with a moving average filter is compared.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"79 1","pages":"302-313"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84118541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1