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۱ نظر موافقین ۰ مخالفین ۰ ۲۴ خرداد ۹۴ ، ۱۱:۲۰

A Fingerprint Technique for Indoor Localization using Autoencoder based Semi-supervised Deep Extreme Learning Machine

Zahra Ezzati Khatab, Amirhosein Hajihoseini Gazestani, Seyed Ali Ghorashi, Mohammad Ghavami

Abstract:

In recent years, because of the growing demand for location based services in indoor environment and development of Wi-Fi, fingerprint-based indoor localization has attracted many researchers’ interest. In Wireless Sensor Networks (WSNs), fingerprint based localization methods estimate the target location by using a pattern matching model for the measurements of the Received Signal Strength (RSS) from the available transmitter sensors, which are collected by a smartphone with internal sensors. Due to the dynamic nature of the environment, the fingerprint database needs to be updated, periodically. Hence, it is better to add new fingerprint data to the primary database in order to update them. However, collecting the labeled data is time consuming and labor intensive. In this paper, we propose a novel algorithm, which uses high level extracted features by an autoencoder to improve the localization performance in the classification process. Furthermore, to update the fingerprint data base, we also add crowd-sourced labeled and unlabeled data in order to improve the localization performance, gradually. Simulation results indicate that the proposed method provides a significant improvement in localization performance, using high level extracted features by the autoencoder, and by increasing the number of unlabeled training data.

Link of Paper

 

۰ نظر موافقین ۰ مخالفین ۰ ۱۳ آذر ۹۹ ، ۲۰:۲۳

Joint Optimization of Power and Location in Full-Duplex UAV Enabled Systems

 Amirhosein Hajihoseini GazestaniSeyed Ali GhorashiZhaohui YangMohammad Shikh-Bahaei

 

Abstract: 

Unmanned aerial vehicles (UAVs) can be used as aerial base stations (BSs) for future small cells. They can increase the spectral efficiency of the small cells due to their higher probability to have line-of-sight (LOS) connections and their mobility as a BS. In this article, in order to show the effectiveness of using full-duplex (FD) technology in UAV networks, we consider a UAV equipped with FD technology (FD-UAV) with imperfect self-interference cancelation as an aerial BS that serves both uplink (UL) and downlink (DL) users simultaneously in a small cell network. We aim to maximize DL sum-rate, whilst prescribing a certain quality of service for UL users, by optimizing the location of FD-UAV and available resources. The problem is nonconvex; so we propose an iterative method by exploiting the difference of convex functions programming to jointly optimize transmission power of users, FD-UAV location, and FD-UAV transmission power. Simulation results are illustrated to show the effectiveness of the proposed method for FD-UAV in comparison with ground BS, in both FD and half-duplex modes.

Link of Paper

۰ نظر موافقین ۰ مخالفین ۰ ۱۳ آذر ۹۹ ، ۱۹:۱۸

Resource Allocation in Full-Duplex UAV Enabled Multi Small Cell Networks

 Amirhosein Hajihoseini Gazestani; Seyed Ali Ghorashi; Zhaohui Yang; Mohammad Shikh-Bahaei

Abstract:

Flying platforms such as Unmanned Aerial Vehicles (UAVs) are a promising solution for future small cell networks. UAVs can be used as aerial Base Stations (BSs) to enhance coverage, capacity and reliability of wireless networks. Also, with recent advances of Self Interference Cancellation (SIC) techniques in Full-Duplex (FD) systems, practical implementation of FD BSs is feasible. In this paper, we investigate the problem of resource allocation for multi-small cell networks with FD-UAVs as aerial BSs with imperfect SIC. We consider three different scenarios: a) maximizing the DL sum-rate, b) maximizing the UL sum-rate, and finally c) maximizing the sum of UL and DL sum-rates. The aforementioned problems result in non-convex optimization problems, therefore, successive convex approximation algorithms are developed by leveraging D.C. (Difference of Convex functions) programming to find sub-optimal solutions. Simulation results illustrated validity and effectiveness of the proposed radio resource management algorithms in comparison with ground BSs, in both FD mode and its half-duplex (HD) counterpart. The results also indicate those situations where using aerial BS is advantageous over ground BS and reveal how FD transmission enhances the network performance in comparison with HD one.

Link of Paper

۰ نظر موافقین ۰ مخالفین ۰ ۱۳ آذر ۹۹ ، ۱۹:۱۵

A compact half butterfly chipless RFID tag based on image theory with DER analysis

 Amirhosein Zarif, Sajad Mohammad-Ali-Nezhad, Sajad Tijeri-Mofrad, Amirhosein Hajihoseini Gazestani

Abstract:

In this paper, a compact RFID chipless structure is designed, simulated, and fabricated. Image theory has been used to reduce the structure of the RFID tag so that it halves the tag and creates a PEC wall having the same resonant frequencies. In other words, each symmetric structure by this method is half the size with features similar to the original structure. The proposed structure has a ratio of area to lambda equal to 0.05 in which there are nine resonances in a frequency band of 4.3–8.5 GHz with dimensions of 14 × 7 mm2 in a bit density of 9.18 bit/cm2 and fabricated on Rog4003 substrate. The bit density for the full structure was equal to 4.59 bit/cm2. The original and proposed structures have similar resonances that indicate the accuracy of the proposed method. Also, this method can be used to create a label with a higher number of bits. The simulation results using HFSS software were in good agreement with the measurement results. Furthermore, the calculated detection error rate of the proposed structure was lower than the original one.

Link of Paper

۰ نظر موافقین ۰ مخالفین ۰ ۱۳ آذر ۹۹ ، ۱۹:۰۹

Throughput improvement by mode selection in hybrid duplex wireless networks

Behnaz Mousavinasab, Amirhosein Hajihoseini Gazestani, Seyed Ali Ghorashi, Mohammad Shikh-Bahaei

Abstract:

Hybrid duplex wireless networks, use half duplex (HD) as well as full duplex (FD) modes to utilize the advantages of both technologies. This paper tries to determine the proportion of the network nodes that should be in HD or FD modes in such networks, to maximize the overall throughput of all FD and HD nodes. Here, by assuming imperfect self-interference cancellation (SIC) and using ALOHA protocol, the local optimum densities of FD, HD and idle nodes are obtained in a given time slot, using Karush–Kuhn–Tucker (KKT) conditions as well as stochastic geometry tool. We also obtain the sub-optimal value of the signal-to-interference ratio (SIR) threshold constrained by fixed node densities, using the steepest descent method in order to maximize the network throughput. The results show that in such networks, the proposed hybrid duplex mode selection scheme improves the level of throughput. The results also indicate the effect of imperfect SIC on reducing the throughput. Moreover, it is demonstrated that by choosing an optimal SIR threshold for mode selection process, the achievable throughput in such networks can increase by around 5%.

Link of Paper

۰ نظر موافقین ۰ مخالفین ۰ ۰۳ خرداد ۹۹ ، ۲۳:۱۴

مروری بر روش ‏های استفاده از فناوری ارتباطات دوطرفه در سامانه‏ های برداشت انرژی

بهناز موسوی نسب، امیرحسین حاجی حسینی گزستانی، سید علی قرشی، محمد شیخ بهایی

چکیده: 

با پیشرفت روزافزون فناوری های الکترونیک و ارتباطات، سامانه ‏های بی‏سیم به عنوان یکی از اجزای جدانشدنی زندگی روزمره مطرح شده و به دنبال آن نیاز به منابع طیفی برای پشتیبانی از تعداد کاربران بیشتر در شبکۀ بی‏سیم، روز به ‏روز افزایش می‏ یابد. با توجه به این افزایشِ نیاز به پهنای باند و جهت استفادۀ کارآمد از ظرفیت ‏های شبکه‏ های بی‏سیم مخابراتی، فناوری «ارتباط دوطرفه» اخیراً در کانون توجه پژوهشگران قرار گرفته است. این فناوری با ارسال و دریافت اطلاعات به صورت همزمان و در یک باند فرکانسی، می‏ تواند بازدهی طیفی را تا دو برابر نسبت به سامانه‏ های یک طرفۀ سنتی بهبود بخشد. از سوی دیگر در سال ‏های اخیر سامانه‏ های برداشت‏ کنندۀ انرژی به عنوان یک راه حل برای رفع مشکل توان مصرفی گره ‏های موجود در شبکه ‏های بی‏سیم مطرح شده‏ اند. در این مقاله ابتدا سناریوهای مختلف به‏ کارگیری فناوری ارتباطات دوطرفه در سامانه‏ های برداشت انرژی مورد بررسی و مقایسه قرار می ‏گیرد، سپس توابع هدف مورد استفاده در طراحی این سامانه ‏ها بررسی می‏ شوند. در انتها نیز چالش ‏های به‏ کارگیری فناوری ارتباط دوطرفه در سامانه ‏های برداشت انرژی مرور خواهد شد.

لینک مقاله

۰ نظر موافقین ۰ مخالفین ۰ ۰۳ خرداد ۹۹ ، ۲۳:۱۰

A Survey on Implementation and Applications of Full Duplex Wireless Communications

Amirhosein Hajihoseini Gazestani, Seyed Ali Ghorashi, Behnaz Mousavinasab, Mohammd Shikh-Bahaei

Abstract

Nowadays, wireless networks play an important role in our daily life. Hence, radio frequency (RF) spectrum which is required to support the large number of users of these networks, have become a very valuable resource. Full Duplex(FD) communications, in which data can be sent and received using the same frequency band at the same time, is a promising solution for satisfying, at least in part, the ever increasing demand for wireless spectrum. Theoretically, FD could double the spectral efficiency and capacity. However, in order to harvest these benefits, it has to combat/suppress self-interference (SI) caused by transmitting and receiving data, simultaneously. FD systems should use SI cancellation methods to deal with this important challenge. Due to the significant benefits of FD communication, this research area has recently attracted much attention among the research community. In this paper, we review the applications and implementation challenges of FD communication in different subject areas such as energy harvesting, vehicular communication, massive Multiple-Input Multiple-Output (MIMO), small cells, practical implementation, millimeter wave and military applications. We also study the tradeoffs in deploying FD communication in each of the applications.

Link of paper

۰ نظر موافقین ۰ مخالفین ۰ ۰۵ فروردين ۹۸ ، ۱۸:۳۷

Distributed Diffusion Based Spectrum Sensing for Cognitive Radio Sensor Networks Considering Link Failure

Amirhosein Hajihoseini Gazestani and Seyed Ali Ghorashi

Abstract:

Wireless sensor networks (WSNs) typically use license free industrial, scientific and medical (ISM) frequency bands and by increasing the demand for different usages of WSNs, it is anticipated that this band gets saturated. One solution to deal with this spectrum scarcity in WSNs is utilizing the cognitive radio concept, called cognitive radio sensor networks (CRSNs). One of the most critical challenges in CRSNs is spectrum sensing, which can be implemented by centralized, cluster based or distributed methods. In CRSNs, distributed methods have better spectrum sensing performance due to their fast adaptation to the network changes. Also they have lower power consumption level, which is critical in CRSNs. In this paper, we propose a novel distributed diffusion based spectrum sensing method for CRSNs that improves the robustness of the spectrum sensing method against link failure and network topology changes. It also increases the algorithm’s convergence rate while its accuracy is acceptable. We prove the proposed method convergence and calculate its mean square error, considering link failure assumption. Simulation results confirm that the proposed method improves the convergence rate compared with conventional distributed methods, and using the proposed method increases the convergence rate and needs less communications to make a decision about absence or presence of the primary user.

link of paper

۰ نظر موافقین ۰ مخالفین ۰ ۰۵ شهریور ۹۷ ، ۰۸:۳۳
Introduction and Patent Analysis of Signal Processing for Big Data
Mohammad Eslami, Amirhosein Hajihoseini Gazestani, Seyed Ali Ghorashi
Abstract: 
Big data is rapidly considered in different scientific domains, industries and business methods. Considering the concept of Internet of Things, big data is generated by everything around us continuously, and therefore, dealing with big data and its challenges are important and requires new thinking strategies and also techniques. Signal processing is one of the solutions that is utilized with big data in most scientific fields. This paper gives a brief introductory preview of the subjects included in this area and describes some of challenges and tactics. In order to show the rapid growth of attentions in signal processing for big data, a statistical analysis on corresponding patents is considered as well.
 
۰ نظر موافقین ۰ مخالفین ۰ ۰۱ شهریور ۹۷ ، ۰۸:۲۹

Image dataset for Persian Road Surface Markings

Seyed Hamid Safavi, Mohammad Eslami, Aliasghar Sharifi, Amirhosein Hajihoseini, Mohammadreza Riahi, Maryam Rekabi, Sadaf Sarrafan, Rahman Zarnoosheh, Ehsan Khodapanah Aghdam, Sahar Barzegari Banadkoki, Seyed Mohammad Seyedin Navadeh, Farah Torkamani-Azar

Abstract:

Self-driving and autonomous cars are hot emerging technologies which can provide enormous impact in the near future. Since an important component of autonomous cars is vision processing, the increasing interest for self-driving cars has motivated researchers to collect different relative image datasets. Hence, we collect a comprehensive dataset about the road surface markings which are available in Iran. In addition, we evaluate the conventional recognition rate. In this paper, we present a novel and extensive dataset for Persian Road Surface Markings (PRSM) with ground truth labels. We also hope that it will be useful as a Persian benchmark dataset for researchers in this field. The dataset consists of over 68,000 labeled images of road markings in 18 popular classes. It also contains road surface markings under various daylight conditions. Our dataset with
further details is available online at: http://display.sbu.ac.ir/databases.

link of paper

۰ نظر موافقین ۰ مخالفین ۰ ۱۲ ارديبهشت ۹۷ ، ۲۳:۰۸

شاخه دانشجویی IEEE دانشکده مهندسی برق دانشگاه شهید بهشتی برگزار می کند:

چهارشنبه پنجم و بیست و نهم اردیبهشت، آمفی تئاتر دانشکده مهندسی برق دانشگاه شهید بهشتی

۰ نظر موافقین ۰ مخالفین ۰ ۲۷ فروردين ۹۷ ، ۱۵:۴۳

A Fingerprint method for Indoor Localization using Autoencoder based Deep Extreme Learning Machine

Zahra Ezzati Khatab, Amirhosein Hajihoseini and Seyed Ali Ghorashi

Abstract:

By growing the demand for location based services in indoor environments in recent years, fingerprint based indoor localization has attracted many researchers' interest. The fingerprint localization method works based on received signal strength (RSS) in Wireless Sensor Networks (WSNs). This methods uses RSS measurements from available transmitter sensors, which are collected by a smart phone with internal sensors. In this paper, we propose a novel algorithm that takes the advantages of deep learning, extreme learning machine (ELM) and high level extracted features by autoencoder, to improve the localization performance in the feature extraction and the classification. Furthermore, as the fingerprint database needs to be updated (due to the dynamic nature of environment), we also increase the number of training data, in order to improve the localization performance, gradually. Simulation results indicate that the proposed method provides a significant improvement in localization performance, by using high level extracted features by autoencoder, and increasing the number of training data.
۰ نظر موافقین ۰ مخالفین ۰ ۱۷ دی ۹۶ ، ۱۰:۲۲

شاخه دانشجویی IEEE دانشکده مهندسی برق دانشگاه شهید بهشتی برگزار می کند:

 پوستر

پنجشنبه بیست و هفتم مهر و چهار آبان، آمفی تئاتر دانشکده مهندسی برق دانشگاه شهید بهشتی

۰ نظر موافقین ۰ مخالفین ۰ ۰۷ مهر ۹۶ ، ۱۰:۲۸

شاخه دانشجویی IEEE دانشکده مهندسی برق دانشگاه شهید بهشتی برگزار می کند:

پوستر

پنجشنبه سیزدهم و بیستم مهرماه، آمفی تئاتر دانشکده مهندسی برق دانشگاه شهید بهشتی

۰ نظر موافقین ۰ مخالفین ۰ ۰۶ مهر ۹۶ ، ۱۲:۰۶

پژوهشکده فضای مجازی دانشگاه شهید بهشتی با همکاری شاخه دانشجویی IEEE برگزار می کند:

پوستر

۰ نظر موافقین ۰ مخالفین ۰ ۰۶ مهر ۹۶ ، ۱۱:۵۹