Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235094
A. M. Mabrouk, S. Zainud-Deen, H. Malhat, A. Ibrahim, H. Hamed
In this paper, reconfigurable polarization converter from linear polarization to circular polarization is designed based on graphene artificial magnetic conductor surface. The reconfigurable conductivity of the graphene material allows the change of electromagnetic wave polarization left-hand and right-hand circular polarization (CP) through electrical DC biasing. The gain enhancement of V-shaped dipole antenna is achieved by backing it with AMC array. The antenna gain is increased up to 4.7 dBi with AMC ground plane. Different AMC ground plane sizes and their effect on polarization conversion are investigated. The polarization conversion bandwidth is 19.44% for 7x7 AMC array. Full-wave analysis is used to model the array structure.
{"title":"Graphene-Based AMC Polarization Converter for Antenna Applications at Microwave Frequency Band","authors":"A. M. Mabrouk, S. Zainud-Deen, H. Malhat, A. Ibrahim, H. Hamed","doi":"10.1109/NRSC49500.2020.9235094","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235094","url":null,"abstract":"In this paper, reconfigurable polarization converter from linear polarization to circular polarization is designed based on graphene artificial magnetic conductor surface. The reconfigurable conductivity of the graphene material allows the change of electromagnetic wave polarization left-hand and right-hand circular polarization (CP) through electrical DC biasing. The gain enhancement of V-shaped dipole antenna is achieved by backing it with AMC array. The antenna gain is increased up to 4.7 dBi with AMC ground plane. Different AMC ground plane sizes and their effect on polarization conversion are investigated. The polarization conversion bandwidth is 19.44% for 7x7 AMC array. Full-wave analysis is used to model the array structure.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"18 1","pages":"16-23"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81046658","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235101
Said E. El Khamy, N. Korany, H. Hassan
A new design of MIMO-OFDM channel estimation using complementary codes is proposed in this paper. In the proposed algorithm a 2x2 space time code MIMO-OFDM system is considered. Instead of using single sided channel estimation techniques as in previous investigation [1], a two-sided approach is considered in. The suggested code on frequency-antenna distribution covers all the OFDM subcarriers. This is an advantage of our algorithm as previous investigations use only half of the subcarriers of the channel estimation. The considered channel model is a multi-tap fading channel model with doppler shift. The simulation results of the proposed algorithm are done assuming multi taps Rayleigh fading channel. Good results are obtained compared to other previous approaches of using complementary code in the estimation of MIMO-OFDM channels at low SNR and channel taps equal one and two.
{"title":"Channel Estimation Techniques for Wideband MIMO-OFDM Communication Systems Using Complementary Codes Two-Sided Sequences","authors":"Said E. El Khamy, N. Korany, H. Hassan","doi":"10.1109/NRSC49500.2020.9235101","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235101","url":null,"abstract":"A new design of MIMO-OFDM channel estimation using complementary codes is proposed in this paper. In the proposed algorithm a 2x2 space time code MIMO-OFDM system is considered. Instead of using single sided channel estimation techniques as in previous investigation [1], a two-sided approach is considered in. The suggested code on frequency-antenna distribution covers all the OFDM subcarriers. This is an advantage of our algorithm as previous investigations use only half of the subcarriers of the channel estimation. The considered channel model is a multi-tap fading channel model with doppler shift. The simulation results of the proposed algorithm are done assuming multi taps Rayleigh fading channel. Good results are obtained compared to other previous approaches of using complementary code in the estimation of MIMO-OFDM channels at low SNR and channel taps equal one and two.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"91 1","pages":"74-84"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82294190","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235095
Mostafa Atlam, Hanaa Torkey, Hanaa Salem, N. El-Fishawy
Accurately classifying medical data is critical for improving diagnostic prediction system and identifying threptic targets for treatments. Analysing gene expression data has a major challenge in extracting disease-related genes from the large number of genes output from next generation sequencing technology. Therefore, eliminating irrelevant and redundant genes is a major step to process data for prediction. Our objective is to predict more accurately the presence of cancer disease in a sample cell from the gene expression.In this paper, we create a function called Classification Technique as Feature Selection (CTFS) as a new feature selection (FS) method to extract a subset (small number) of genes from classified big number of genes expression to improve cancer prediction result. The enrolled classification techniques in CTFS function for selection are K-Nearest Neighbors (K-NN) and Extreme Gradient Boosting (XGBoosting) optimized by Bayesian Parameter Tuning (BPT). The feature selection methods used to investigate the performance of CTFS function are Univariate Feature Selection (UFS) and Feature Importance (FI). The classification stage is carried out after the feature selection stage using three machine learning (ML) algorithms, Naïve Bayes (NB), Linear Support Vector Machine (LSVM), and Random Forest (RF). Results shows that, using XGBoosting optimized by BPT for FS outperforms FI method in terms of increasing the prediction accuracies along with minimum number of features but with higher running time. The performance of K-NN in FS outperforms all other FS methods in terms of accuracies providing an accuracy that is up to 100% when applied with LSVM on simulation dataset.
医学数据的准确分类是完善诊断预测系统和确定治疗目标的关键。从下一代测序技术输出的大量基因中提取疾病相关基因是分析基因表达数据的一大挑战。因此，消除不相关和冗余的基因是处理数据进行预测的重要步骤。我们的目标是通过基因表达更准确地预测样本细胞中癌症疾病的存在。本文提出了一种新的特征选择方法，即CTFS (Classification Technique as Feature Selection)，从分类的大量基因表达中提取出一个子集(少量)的基因，以提高癌症预测结果。CTFS函数中用于选择的分类技术包括k -最近邻(K-NN)和贝叶斯参数调优(BPT)优化的极限梯度增强(XGBoosting)。用于研究CTFS函数性能的特征选择方法是单变量特征选择(UFS)和特征重要性(FI)。分类阶段在特征选择阶段之后进行，使用三种机器学习(ML)算法，Naïve贝叶斯(NB)，线性支持向量机(LSVM)和随机森林(RF)。结果表明，使用BPT优化的XGBoosting方法在提高预测精度和特征数量最少的情况下优于FI方法，但运行时间更长。在精度方面，K-NN在FS中的性能优于所有其他FS方法，当在模拟数据集上使用LSVM时，提供高达100%的精度。
{"title":"A New Feature Selection Method for Enhancing Cancer Diagnosis Based on DNA Microarray","authors":"Mostafa Atlam, Hanaa Torkey, Hanaa Salem, N. El-Fishawy","doi":"10.1109/NRSC49500.2020.9235095","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235095","url":null,"abstract":"Accurately classifying medical data is critical for improving diagnostic prediction system and identifying threptic targets for treatments. Analysing gene expression data has a major challenge in extracting disease-related genes from the large number of genes output from next generation sequencing technology. Therefore, eliminating irrelevant and redundant genes is a major step to process data for prediction. Our objective is to predict more accurately the presence of cancer disease in a sample cell from the gene expression.In this paper, we create a function called Classification Technique as Feature Selection (CTFS) as a new feature selection (FS) method to extract a subset (small number) of genes from classified big number of genes expression to improve cancer prediction result. The enrolled classification techniques in CTFS function for selection are K-Nearest Neighbors (K-NN) and Extreme Gradient Boosting (XGBoosting) optimized by Bayesian Parameter Tuning (BPT). The feature selection methods used to investigate the performance of CTFS function are Univariate Feature Selection (UFS) and Feature Importance (FI). The classification stage is carried out after the feature selection stage using three machine learning (ML) algorithms, Naïve Bayes (NB), Linear Support Vector Machine (LSVM), and Random Forest (RF). Results shows that, using XGBoosting optimized by BPT for FS outperforms FI method in terms of increasing the prediction accuracies along with minimum number of features but with higher running time. The performance of K-NN in FS outperforms all other FS methods in terms of accuracies providing an accuracy that is up to 100% when applied with LSVM on simulation dataset.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"44 1","pages":"285-295"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84630996","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235098
Doaa K. Elswah, A. Elnakib, Hossam El-Din Moustafa
This paper presents a deep learning framework for the classification of diabetic retinopathy (DR) grades from fundus images. The proposed framework is composed of three stages. First, the fundus image is preprocessed using intensity normalization and augmentation. Second, the pre-processed image is input to a ResNet Convolutional Neural Network (CNN) model in order to extract a compact feature vector for grading. Finally, a classification step is used to detect DR and determine its grade (e.g., mild, moderate, severe, or Proliferative Diabetic Retinopathy (PDR)). The proposed framework is trained using the challenging ISBI’2018 Indian Diabetic Retinopathy Image Dataset (IDRiD). To remove the training bias, the data is balanced to ensure that each DR grade is represented with the same number of images during the training process. The proposed system shows an improved performance with respect to the related techniques using the same data, evidenced by the highest overall classification accuracy of 86.67%.
{"title":"Automated Diabetic Retinopathy Grading using Resnet","authors":"Doaa K. Elswah, A. Elnakib, Hossam El-Din Moustafa","doi":"10.1109/NRSC49500.2020.9235098","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235098","url":null,"abstract":"This paper presents a deep learning framework for the classification of diabetic retinopathy (DR) grades from fundus images. The proposed framework is composed of three stages. First, the fundus image is preprocessed using intensity normalization and augmentation. Second, the pre-processed image is input to a ResNet Convolutional Neural Network (CNN) model in order to extract a compact feature vector for grading. Finally, a classification step is used to detect DR and determine its grade (e.g., mild, moderate, severe, or Proliferative Diabetic Retinopathy (PDR)). The proposed framework is trained using the challenging ISBI’2018 Indian Diabetic Retinopathy Image Dataset (IDRiD). To remove the training bias, the data is balanced to ensure that each DR grade is represented with the same number of images during the training process. The proposed system shows an improved performance with respect to the related techniques using the same data, evidenced by the highest overall classification accuracy of 86.67%.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"30 1","pages":"248-254"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87780194","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235089
M. Ismail, A. R. Eldamak, H. Ghali
This paper introduces design, fabrication and measurements for a printed meander dipole antenna with enhanced -10 dB bandwidth of 20 MHz (13%) in the VHF band. The antenna is fabricated on FR4 substrate with an overall compact area of 61.3 cm X 6.45 cm. The dipole antenna is composed of meander line terminated with a stub. Bandwidth enhancement is realized through two techniques; 1) resistive loading to the meander line, and 2) metal strips at the back side acting as capacitive loading. A parametric study is implemented for the position, values of the resistors and the dimensions of the metal strips to realize maximum bandwidth. Using resistive loading, the bandwidth is increased from 6.6 MHz to 12 MHz with efficiency 42 %. On the other hand, adding two metal strips further increases the bandwidth to 20 MHz with efficiency up to 56%. The antenna exhibits omnidirectional radiation characteristics over the operating frequency band 140-160 MHz. The proposed structure is fabricated, measured and compared to simulated results, where measurements are in good agreement with simulation results.
本文介绍了一种在VHF频段中-10 dB带宽增强为20 MHz(13%)的印刷弯曲偶极子天线的设计、制作和测量。天线在FR4基板上制作，整体紧凑面积为61.3 cm X 6.45 cm。偶极天线由端接短根的曲线组成。带宽增强通过两种技术实现;1)曲线上的电阻性负载，2)背面的金属条作为电容性负载。为了实现最大带宽，对电阻的位置、值和金属条的尺寸进行了参数化研究。通过电阻加载，带宽从6.6 MHz增加到12 MHz，效率提高42%。另一方面，增加两个金属条将带宽进一步提高到20 MHz，效率高达56%。该天线在工作频段140-160 MHz范围内具有全向辐射特性。所提出的结构进行了制作、测量并与模拟结果进行了比较，其中测量结果与模拟结果吻合良好。
{"title":"Bandwidth Enhancement For Meander Dipole Antenna in MHz range","authors":"M. Ismail, A. R. Eldamak, H. Ghali","doi":"10.1109/NRSC49500.2020.9235089","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235089","url":null,"abstract":"This paper introduces design, fabrication and measurements for a printed meander dipole antenna with enhanced -10 dB bandwidth of 20 MHz (13%) in the VHF band. The antenna is fabricated on FR4 substrate with an overall compact area of 61.3 cm X 6.45 cm. The dipole antenna is composed of meander line terminated with a stub. Bandwidth enhancement is realized through two techniques; 1) resistive loading to the meander line, and 2) metal strips at the back side acting as capacitive loading. A parametric study is implemented for the position, values of the resistors and the dimensions of the metal strips to realize maximum bandwidth. Using resistive loading, the bandwidth is increased from 6.6 MHz to 12 MHz with efficiency 42 %. On the other hand, adding two metal strips further increases the bandwidth to 20 MHz with efficiency up to 56%. The antenna exhibits omnidirectional radiation characteristics over the operating frequency band 140-160 MHz. The proposed structure is fabricated, measured and compared to simulated results, where measurements are in good agreement with simulation results.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"CE-23 1","pages":"24-29"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84564540","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235097
N. Elmenabawy, A. Elnakib, H. Moustafa
A framework is proposed for joint liver and cancerous nodule segmentation from abdomen computed tomography (CT) images. The proposed framework consists of three main units. First, a preprocessing unit is used to enhance the image contrast. Second, two different deep convolutional-deconvolutional neural networks (CDNN), namely, Alexnet and Resnet18 models, are investigated to extract the features of liver images. Finally, a pixel wise classification unit is performed to provide the final segmentation maps of the liver and tumors. Results on the challenging MICCAI’2017 liver tumor segmentation (LITS) database, using Alexnet model and 4-fold cross-validation, achieve a Dice similarity coefficient of 90.4% for liver segmentation and of 62.4% for lesion segmentation. Comparative results with related techniques for joint liver and tumor segmentations show the effectiveness of the proposed framework.
{"title":"Deep Joint Segmentation of Liver and Cancerous Nodules From Ct Images","authors":"N. Elmenabawy, A. Elnakib, H. Moustafa","doi":"10.1109/NRSC49500.2020.9235097","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235097","url":null,"abstract":"A framework is proposed for joint liver and cancerous nodule segmentation from abdomen computed tomography (CT) images. The proposed framework consists of three main units. First, a preprocessing unit is used to enhance the image contrast. Second, two different deep convolutional-deconvolutional neural networks (CDNN), namely, Alexnet and Resnet18 models, are investigated to extract the features of liver images. Finally, a pixel wise classification unit is performed to provide the final segmentation maps of the liver and tumors. Results on the challenging MICCAI’2017 liver tumor segmentation (LITS) database, using Alexnet model and 4-fold cross-validation, achieve a Dice similarity coefficient of 90.4% for liver segmentation and of 62.4% for lesion segmentation. Comparative results with related techniques for joint liver and tumor segmentations show the effectiveness of the proposed framework.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"34 1","pages":"296-301"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88435577","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235114
A. M. Ameen, B. M. Yousef, A. Attiya
A new design of significant mutual coupling reduction antennas using metamaterial structure (MTM) is introduced. The technique which is used to reduce the coupling is complementary split ring resonator (CSRR) loaded between the two microstrip patches. The proposed antenna is designed to be operate at frequency of 28GHz. This structure suitable to operate in 5G and mm-wave antenna systems. A significant improvement in coupling between antennas is obtained. The maximum isolation achieved by etching the CSRR on the ground of the proposed antenna and on a floated ground between the two patched is 31.7dB. The distance from edge-to-edge of the patch antennas is 0.4λ0. In addition to design and simulate the proposed antenna using CST program, it is also fabricated and measured. Good agreements is achieved between simulated and measured results.
{"title":"Mutual Coupling Reduction Between MM-Wave Microstrip Antennas Using CSRR Metamaterial Structure","authors":"A. M. Ameen, B. M. Yousef, A. Attiya","doi":"10.1109/NRSC49500.2020.9235114","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235114","url":null,"abstract":"A new design of significant mutual coupling reduction antennas using metamaterial structure (MTM) is introduced. The technique which is used to reduce the coupling is complementary split ring resonator (CSRR) loaded between the two microstrip patches. The proposed antenna is designed to be operate at frequency of 28GHz. This structure suitable to operate in 5G and mm-wave antenna systems. A significant improvement in coupling between antennas is obtained. The maximum isolation achieved by etching the CSRR on the ground of the proposed antenna and on a floated ground between the two patched is 31.7dB. The distance from edge-to-edge of the patch antennas is 0.4λ0. In addition to design and simulate the proposed antenna using CST program, it is also fabricated and measured. Good agreements is achieved between simulated and measured results.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"7 1","pages":"48-56"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82007755","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235104
A. M. Mahfouz, O. Haraz, A. Ibraheem
Loop antennas have low specific absorption rate (SAR) and immune against the changes of the electrical properties of the human body. Electrically coupled loop antenna (ECLA) has been introduced as a dual for PIFA for single and multiband operation. To miniaturize ECLA, lumped capacitors have been used. However, this miniaturization technique has alignment problems, especially for multiband operation. Through this paper, a novel miniaturization technique is introduced. The proposed method depends on increasing loop inductance through wrapping another loop in addition to increasing matching capacitor which formed by the overlapped loops. The proposed antenna with size of 13×13×3mm3 has been simulated inside human head model and designed to operate at medical implants communications services (MICS) 402-405 MHz and industrial scientific medical (ISM) 2.4-2.48 GHz bands without lumped capacitors. The peak value of the 1 gm averaged SAR is 92.8 and 105.6 W/Kg whereas the peak realized gain is -29.5 and -22.5 dbi for both bands, respectively.
{"title":"A Miniaturized Dual Band Rectangular Spiral Loop Antenna for Biomedical Implants","authors":"A. M. Mahfouz, O. Haraz, A. Ibraheem","doi":"10.1109/NRSC49500.2020.9235104","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235104","url":null,"abstract":"Loop antennas have low specific absorption rate (SAR) and immune against the changes of the electrical properties of the human body. Electrically coupled loop antenna (ECLA) has been introduced as a dual for PIFA for single and multiband operation. To miniaturize ECLA, lumped capacitors have been used. However, this miniaturization technique has alignment problems, especially for multiband operation. Through this paper, a novel miniaturization technique is introduced. The proposed method depends on increasing loop inductance through wrapping another loop in addition to increasing matching capacitor which formed by the overlapped loops. The proposed antenna with size of 13×13×3mm3 has been simulated inside human head model and designed to operate at medical implants communications services (MICS) 402-405 MHz and industrial scientific medical (ISM) 2.4-2.48 GHz bands without lumped capacitors. The peak value of the 1 gm averaged SAR is 92.8 and 105.6 W/Kg whereas the peak realized gain is -29.5 and -22.5 dbi for both bands, respectively.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"196 1","pages":"264-268"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79883593","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235121
Michael Ibrahim
In this paper, the task of performing finite-length minimum mean square error (MMSE) equalization is considered for single carrier communication systems. A detailed mathematical derivation of the finite-length MMSE equalizer is presented where the MMSE equalizer coefficients are described using linear convolution instead of the matrix form representation, which is commonly found in literature. The linear convolution is then transformed into circular convolution by performing frequency-domain sampling while avoiding time-domain aliasing. The computation of the circular convolution naturally lends itself to employing FFT and IFFT operations, which leads to a significant complexity reduction compared to the traditional approaches of computing the MMSE equalizer coefficients using matrix inversion.
{"title":"Complexity Reduction of Finite-Length MMSE Equalization Using FFT","authors":"Michael Ibrahim","doi":"10.1109/NRSC49500.2020.9235121","DOIUrl":"https://doi.org/10.1109/NRSC49500.2020.9235121","url":null,"abstract":"In this paper, the task of performing finite-length minimum mean square error (MMSE) equalization is considered for single carrier communication systems. A detailed mathematical derivation of the finite-length MMSE equalizer is presented where the MMSE equalizer coefficients are described using linear convolution instead of the matrix form representation, which is commonly found in literature. The linear convolution is then transformed into circular convolution by performing frequency-domain sampling while avoiding time-domain aliasing. The computation of the circular convolution naturally lends itself to employing FFT and IFFT operations, which leads to a significant complexity reduction compared to the traditional approaches of computing the MMSE equalizer coefficients using matrix inversion.","PeriodicalId":6778,"journal":{"name":"2020 37th National Radio Science Conference (NRSC)","volume":"26 1","pages":"137-144"},"PeriodicalIF":0.0,"publicationDate":"2020-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84804114","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}
Pub Date : 2020-09-08DOI: 10.1109/NRSC49500.2020.9235118
Weaam T. EL-Gzzar, Hala B. Nafea, F. Zaki
The wireless sensor network (WSN) is a network composed of spatially distributed sensors which communicate among themselves for detecting and recording the physical phenomenon (like temperature, sound, pollution levels, humidity, wind speed, pressure, and so on) and organizing the collected data at a central location. Due to the use of WSN in various applications, knowing the location of the object or event is one of the most important challenges in WSN, which is called the localization process. In this paper, received signal strength indicator (RSSI) and angle of arrival (AOA) algorithms are considered for the WSN localization process. Moreover, a new method based on AOA localization techniques with dynamic distance reference anchor has been presented and the problem of localization accuracy which is affected by environmental conditions is improved. The proposed algorithm is implemented into a near ground radio propagation channel of agriculture farm (short and tall grass). It is found that the new localization method provides the best results as compared with conventional methods.
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