arXiv subjects

Soo Young Shin

Publications and source records attributed to Soo Young Shin.

At least 19 recordsLinked to original sources

arXiv2022

Massive MIMO NOMA with Wavelet Pulse Shaping to Minimize Undesired Channel Interference

In this article, wavelet OFDM based non-orthogonal-multiple-access (NOMA) combined with massive MIMO system for 6G networks is proposed. For mMIMO transmissions, the proposed system could enhance the performance by utilizing wavelets to compensate for channel impairments on the transmitted signal. Performance measures include spectral efficiency, symbol error rate (SER), and peak to average ratio (PAPR). Simulation results prove that the proposed system outperforms the conventional OFDM based NOMA systems.

cs.IT↗

arXiv2021

Real-Time Trash Detection for Modern Societies using CCTV to Identifying Trash by utilizing Deep Convolutional Neural Network

To protect the environment from trash pollution, especially in societies, and to take strict action against the red-handed people who throws the trash. As modern societies are developing and these societies need a modern solution to make the environment clean. Artificial intelligence (AI) evolution, especially in Deep Learning, gives an excellent opportunity to develop real-time trash detection using CCTV cameras. The inclusion of this project is real-time trash detection using a deep model of Convolutional Neural Network (CNN). It is used to obtain eight classes mask, tissue papers, shoppers, boxes, automobile parts, pampers, bottles, and juices boxes. After detecting the trash, the camera records the video of that person for ten seconds who throw trash in society. The challenging part of this paper is preparing a complex custom dataset that took too much time. The dataset consists of more than 2100 images. The CNN model was created, labeled, and trained. The detection time accuracy and average mean precision (mAP) benchmark both models' performance. In experimental phase the mAP performance and accuracy of the improved CNN model was superior in all aspects. The model is used on a CCTV camera to detect trash in real-time.

cs.CV↗

arXiv2021

Performance Evaluation of Cooperative NOMA-based Improved Hybrid SWIPT Protocol

This study proposes the integration of a cooperative non-orthogonal multiple access (CNOMA) and improved hybrid simultaneous wireless information and power transfer (IHS SWIPT) protocol (termed as CNOMA-IHS) to enhance the spectral efficiency (SE) of a downlink (DL) CNOMA communication system. CNOMA-IHS scheme can enhance the ergodic sum capacity (ESC) and energy efficiency (EE) of DL CNOMA by transferring additional symbols towards the users and energize the relay operation as well without any additional resources (e.g., time slot/frequency/code). The analytical and simulation results indicate that the proposed CNOMA-IHS scheme outperforms other existing SWIPT-based schemes (e.g., CNOMA with hybrid SWIPT, CNOMA with power-splitting SWIPT, wireless-powered CNOMA, CNOMA with time switching SWIPT, and orthogonal multiple access with IHS SWIPT) in terms of the ESC. Moreover, the CNOMA-IHS scheme also enhances EE compared with other conventional TS-SWIPT-based schemes, which is also illustrated by the simulation results. In addition, the proposed CNOMA-IHS scheme with the considered EE optimization technique outplayed the proposed CNOMA-IHS scheme without EE optimization and other existing TS-SWIPT-based schemes in terms of EE.

cs.IT↗

arXiv2020

Energy Efficient Pairing and Power Optimization for NOMA UAV Network under QoS Constraints

Due to an increasing number of unmanned aerial vehicles (UAVs) with generally limited battery power, energy efficient data transmission schemes with massive connectivity capabilities are required for future wireless networks. Non-orthogonal multiple access (NOMA) is one of the promising techniques that provide such massive connectivity by allowing superposed data transmission of multiple users over the same resource block. Unlike existing literature, this paper presents a user pairing and power allocation technique for energy efficient and quality of service (QoS) aware NOMA transmission for cellular-connected mobile UAVs. The aim is to minimize the power consumption of the mobile UAVs during uplink data transmission and guarantee their required transmission rate by jointly optimizing the UAV pairing and power allocation. Furthermore, the performance and pairing complexity for mobile UAVs is analyzed to show that the proposed pairing technique efficiently fulfills their QoS requirements. Numerical and simulation results show the performance gain of the proposed technique compared to the conventional NOMA techniques.

eess.SP↗

arXiv2020

A Deep Convolutional Neural Network for the Detection of Polyps in Colonoscopy Images

Computerized detection of colonic polyps remains an unsolved issue because of the wide variation in the appearance, texture, color, size, and presence of the multiple polyp-like imitators during colonoscopy. In this paper, we propose a deep convolutional neural network based model for the computerized detection of polyps within colonoscopy images. The proposed model comprises 16 convolutional layers with 2 fully connected layers, and a Softmax layer, where we implement a unique approach using different convolutional kernels within the same hidden layer for deeper feature extraction. We applied two different activation functions, MISH and rectified linear unit activation functions for deeper propagation of information and self regularized smooth non-monotonicity. Furthermore, we used a generalized intersection of union, thus overcoming issues such as scale invariance, rotation, and shape. Data augmentation techniques such as photometric and geometric distortions are adapted to overcome the obstacles faced in polyp detection. Detailed benchmarked results are provided, showing better performance in terms of precision, sensitivity, F1- score, F2- score, and dice-coefficient, thus proving the efficacy of the proposed model.

cs.CV↗

arXiv2020

New Normal: Cooperative Paradigm for Covid-19 Timely Detection and Containment using Internet of Things and Deep Learning

The spread of the novel coronavirus (COVID-19) has caused trillions of dollars in damages to the governments and health authorities by affecting the global economies. The purpose of this study is to introduce a connected smart paradigm that not only detects the possible spread of viruses but also helps to restart businesses/economies, and resume social life. We are proposing a connected Internet of Things ( IoT) based paradigm that makes use of object detection based on convolution neural networks (CNN), smart wearable and connected e-health to avoid current and future outbreaks. First, connected surveillance cameras feed continuous video stream to the server where we detect the inter-object distance to identify any social distancing violations. A violation activates area-based monitoring of active smartphone users and their current state of illness. In case a confirmed patient or a person with high symptoms is present, the system tracks exposed and infected people and appropriate measures are put into actions. We evaluated the proposed scheme for social distancing violation detection using YOLO (you only look once) v2 and v3, and for infection spread tracing using Python simulation.

cs.CY↗

arXiv2020

An Improved Deep Convolutional Neural Network-Based Autonomous Road Inspection Scheme Using Unmanned Aerial Vehicles

Advancements in artificial intelligence (AI) gives a great opportunity to develop an autonomous devices. The contribution of this work is an improved convolutional neural network (CNN) model and its implementation for the detection of road cracks, potholes, and yellow lane in the road. The purpose of yellow lane detection and tracking is to realize autonomous navigation of unmanned aerial vehicle (UAV) by following yellow lane while detecting and reporting the road cracks and potholes to the server through WIFI or 5G medium. The fabrication of own data set is a hectic and time-consuming task. The data set is created, labeled and trained using default and an improved model. The performance of both these models is benchmarked with respect to accuracy, mean average precision (mAP) and detection time. In the testing phase, it was observed that the performance of the improved model is better in respect of accuracy and mAP. The improved model is implemented in UAV using the robot operating system for the autonomous detection of potholes and cracks in roads via UAV front camera vision in real-time.

cs.CV↗

arXiv2020

Deep-Learning-Aided Detection for Reconfigurable Intelligent Surfaces

This paper presents a deep learning (DL) approach for estimating and detecting symbols in signals transmitted through reconfigurable intelligent surfaces (RIS). The proposed network utilizes fully connected layers to estimate channels and phase angles from a reflected signal received through an RIS. Because the proposed network can estimate and detect symbols without any pilot signaling, this method reduces the overhead required for transmission. The improvements achieved by this method are quantified in terms of the bit-error rate, outperforming traditional detectors.

eess.SP↗

arXiv2020

Comparing H.265/HEVC and VP9: Impact of High Frame Rates on the Perceptual Quality of Compressed Videos

High frame rates have been known to enhance the perceived visual quality of specific video content. However, the lack of investigation of high frame rates has restricted the expansion of this research field particularly in the context of full-high-definition (FHD) and 4K ultra-high-definition video formats. This study involves a subjective and objective quality assessment of compressed FHD videos. First, we compress the FHD videos by employing high-efficiency video coding, and VP9 at five quantization parameter levels for multiple frame rates, i.e., 15fps, 30fps, and 60fps. The FHD videos are obtained from a high frame-rate video database BVI-HFR, spanning various scenes, colors, and motions, and are shown to be representative of the BBC broadcast content. Second, a detailed subjective quality assessment of compressed videos for both encoders and individual frame rates is conducted, resulting in subjective measurements in the form of the differential mean opinion score reflecting the quality of experience. In particular, the aim is to investigate the impact of compression on the perceptual quality of compressed FHD videos and compare the performance of both encoders for each frame rate. Finally, 11 state-of-the-art objective quality assessment metrics are benchmarked using the subjective measurements, to investigate the correlation as a statistical evaluation between the two models in terms of correlation coefficients. A recommendation for enhancing the quality estimation of full-reference (FR) video quality measurements (VQMs) is presented after the extensive investigation.

eess.IV↗

arXiv2020

Exploiting non-orthogonal multiple access in downlink coordinated multipoint transmission with the presence of imperfect channel state information

In this paper, the impact of imperfect channel state information (CSI) on a downlink coordinated multipoint (CoMP) transmission system with non-orthogonal multiple access (NOMA) is investigated since perfect knowledge of a channel can not be guaranteed in practice. Furthermore, the channel estimation error is applied to estimate the channel information wherein its priori of variance is assumed to be known. The impact of the number of coordinated base stations (BSs) on downlink CoMP NOMA is investigated. Users are classified into one of two groups according to their position within the cell, namely cell-center user (CCU) and cell-edge user (CEU). In this paper, ergodic capacity and sum capacity for both CCU and CEU are derived as closed form. In addition, various experiments are conducted with different parameters such as SNR, error variance, and power allocation to show their impact on the CoMP method. The results show that CoMP NOMA outperforms the CoMP orthogonal multiple access (OMA) wherein the condition of the channel impacts the performance of CoMP NOMA less. It is worth noting that a higher number of coordinated BSs enhances the total capacity of CoMP NOMA. Finally, the performance analysis is validated due to the close accordance between the analytical and simulation results.

cs.IT↗

arXiv2019

Role Switching and Power Allocation Technique for Mobile Users in NOMA

In this letter, role switching and power allocation schemes are proposed to tackle user mobility in non-orthogonal multiple access (NOMA) systems. When cell center user (CCU) and cell edge user (CEU) come very close or even cross each other in NOMA pairing, channel gains of paired users violate the basic NOMA conditions. This article refers to such condition as NOMA principle violation problem (NPVP). To solve this NPVP, optimized power role switching-NOMA (OPRS-NOMA) technique is proposed. Role switching technique is used where roles of mobile users are switched on the basis of their channel gains. Furthermore, a power allocation scheme based on bisection search power optimization is presented to maximize the average sum capacity of mobile NOMA users. Random way point mobility model is considered for user mobility. Individual and sum capacity are used for performance evaluation. Simulation results show that OPRS-NOMA outperforms the conventional NOMA and orthogonal multiple access (OMA).

eess.SP↗

arXiv2019

Capacity improvement of non-orthogonal multiple access downlink transmission by orbital angular momentum based mode division multiple access

In this paper, non-orthogonal multiple access (NOMA) downlink transmission is integrated with orbital angular momentum (OAM) based mode division multiple access (MDMA), called NOMA-OAM-MDMA. Different OAM modes can generate different OAM waves for different superimposed signals. So, every OAM wave will be transmitted a superimposed signal from the base station to the cell center user (CCU) and cell edge user (CEU). In this way, multiple OAM waves with multiple superimposed signals will transmit from BS to CCU and CEU simultaneously to enhance the capacity of NOMA downlink transmission. Finally, the effectiveness of the proposed schemes over the existing scheme and conventional orthogonal multiple access based scheme are demonstrated through the result analysis.

cs.NI↗

arXiv2019

Channel Capacity Enhancement of SWIPT based CNOMA Downlink Transmission with Orbital Angular Momentum over Rician Fading Channel

In this paper, the integration of cooperative non-orthogonal multiple access (CNOMA) and power splitting based simultaneous wireless information and power transfer (SWIPT) is proposed to improve the spectral and energy efficiency. Moreover, different orbital angular momentum (OAM) based signals are also considered in this paper to transmit additional symbols to cell center user (CCU) and cell edge user (CEU). In the proposed technique, CCU is used as energy-constrained relay to forward signal to CEU. CCU harvests energy from the transmitted signal by the BS using the power splitting technique. The additional symbols are transmitted from the BS to CCU and CEU by utilizing different modes of OAM. This paper investigates the ergodic sum capacity (ESC) of the proposed technique along with analytical derivations over Rician fading channels. Finally, the performance in terms of ESC and energy efficiency over conventional technique compared to conventional multiple access is demonstrated by analysis and simulation.

cs.NI↗

arXiv2019

A Survey on Contemporary Computer-Aided Tumor, Polyp, and Ulcer Detection Methods in Wireless Capsule Endoscopy Imaging

Wireless capsule endoscopy (WCE) is a process in which a patient swallows a camera-embedded pill-shaped device that passes through the gastrointestinal (GI) tract, captures and transmits images to an external receiver. WCE devices are considered as a replacement of conventional endoscopy methods which are usually painful and distressful for the patients. WCE devices produce over 60,000 images typically during their course of operation inside the GI tract. These images need to be examined by expert physicians who attempt to identify frames that contain inflammation / disease. It can be hectic for a physician to go through such a large number of frames, hence computer-aided detection methods are considered an efficient alternative. Various anomalies can take place in the GI tract of a human being but the most important and common ones and the aim of this survey are ulcers, polyps, and tumors. In this paper, we have presented a survey of contemporary computer-aided detection methods that take WCE images as input and classify those images in a diseased/abnormal or disease-free/ normal image. We have considered methods that detect tumors, polyps and ulcers, as these three diseases lie in the same category. Furthermore bleeding inside the GI tract may be the symptoms of these diseases; so an attempt is also made to enlighten the research work done for bleeding detection inside WCE. Several studies have been included with in-depth detail of their methodologies, findings, and conclusions. Also, we have attempted to classify these methods based on their technical aspects. This paper also includes a potential proposal for joint classification of aforementioned three diseases.

eess.IV↗

arXiv2019

Non-Orthogonal Multiple Access with Spatial Modulation in Downlink Coordinated Multipoint Transmission

In this paper, a joint transmission coordinated multi-point based non-orthogonal multiple access (JT-COMP NOMA) combined with spatial modulation (SM), termed as JT-COMP NOMA-SM, is proposed to enhance capacity. User capacity and ergodic sum capacity (ESC) of M number coordinated multi-point base stations (COMP BSs) within N number of cells are analyzed by considering imperfect successive interference cancellation (SIC) and imperfect channel state information (CSI). The performances of the proposed syatem are compared with non-orthogonal multiple access (NOMA), and joint transmission coordinated multi-point combined with virtual user pairing based non-orthogonal multiple access (JT-COMP VP-NOMA) by both simulation and analysis. The results show that the proposed system has the same cell center user (CCU) capacity compared to JT-COMP VP-NOMA and a higher cell edge user (CEU) capacity than the other schemes. ESC of the proposed system outperforms the other schemes due to enhancing CEU capacity. Imperfect SIC and imperfect CSI may degrade capacity. The proposed system can maintain CEU capacity better than the other schemes if the number of cells is increased. It happens because SM works beyond Shannon upper bounds which can mitigate inter-cell interference (ICI).

cs.IT↗

arXiv2019

Capacity Enhancement of Cooperative NOMA over Rician Fading Channels with Orbital Angular Momentum

This letter proposes the usage of orbital angular momentum (OAM) for cooperative non-orthogonal multiple access (CNOMA) to enhance sum capacity (SC) for the future cellular communication system. The proposed CNOMA-OAM scheme is analyzed and compared with other schemes, i.e., conventional CNOMA, conventional orthogonal multiple access (OMA) with OAM. The impact of the power allocation factor for OAM beam over SC is also analyzed. The analytical result is justified by simulation results which demonstrate that the proposed CNOMA-OAM provides higher SC compared to other schemes.

eess.SP↗

arXiv2019

NEWSTRADCOIN: A Blockchain Based Privacy Preserving Secure NEWS Trading Network

In order to stay up to date with world issues and cutting-edge technol-ogies, the newspaper plays a crucial role. However, collecting news is not a very easy task. Currently, news publishers are collecting news from their correspond-ents through social networks, email, phone call, fax etc. and sometimes they buy news from the agencies. However, the existing news sharing networks may not provide security for data integrity and any third party may obstruct the regular flow of news sharing. Moreover, the existing news schemes are very vulnerable in case of disclosing the identity. Therefore, a universal platform is needed in the era of globalization where anyone can share and trade news from anywhere in the world securely, without the interference of third-party, and without disclosing the identity of an individual. Recently, blockchain has gained popularity because of its security mechanism over data, identity, etc. Blockchain enables a distrib-uted way of managing transactions where each participant of the network holds the same copy of the transactions. Therefore, with the help of pseudonymity, fault-tolerance, immutability and the distributed structure of blockchain, a scheme (termed as NEWSTRADCOIN) is presented in this paper in which not only news can be shared securely but also anyone can earn money by selling news. The proposed NEWSTRADCOIN can provide a universal platform where publishers can directly obtain news from news-gatherers in a secure way by main-taining data integrity, without experiencing the interference of a third-party, and without disclosing the identity of the news gatherer and publishers.

cs.NI↗

arXiv2019

Virtual User Pairing Non-Orthogonal Multiple Access in Downlink Coordinated Multipoint Transmission

In this paper, joint transmission coordinated multipoint (JT-CoMP) is exploited by using virtual user pairing non-orthogonal multiple access (VP-NOMA), termed as JT-CoMP VP-NOMA. The technique combines both VP-NOMA for enhancing ergodic sum capacity (ESC) and JT-CoMP for inter-cell interference mitigation. To show the performance gains, ESC of a three-cell scenario is analyzed as a key performance metric. The analytical and simulation results of JT-CoMP VP-NOMA are compared with orthogonal multiple access (OMA), non-orthogonal multiple access (NOMA), and VP-NOMA. It is shown that the proposed JT-CoMP VP-NOMA outperforms the other schemes in the viewpoint of ESC.

cs.NI↗