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

Journal paper
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.

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

Journal paper
Amirhosein Hajihoseini Gazestani; Seyed Ali Ghorashi; Zhaohui Yang; Mohammad 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.

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

Journal paper
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.

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

Journal paper
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.

5- Throughput improvement by mode selection in hybrid duplex wireless networks

Journal paper
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%.

 

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

Journal paper
بهناز موسوی نسب، امیرحسین حاجی حسینی گزستانی، سیدعلی 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.

کلیدواژه ها

ارتباط دوطرفه؛ برداشت انرژی؛ انتقال بی‏سیم توان؛ سامانه ‏های SWIPT (انتقال بی‏سیم اطلاعات و توان به صورت همزمان)

7- A Survey on Implementation and Applications of Full Duplex Wireless Communications

Journal paper
Amirhosein Hajihoseini Gazestani, Seyed Ali Ghorashi, Behnaz Mousavinasab, Mohammad Shik-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.

Keywords

Full duplex, Energy harvesting, Vehicular communications, Massive MIMO, Small cells, Practical implementation, Millimeter wave, Military.

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

Journal paper
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.
Keywords: 
Distributed, Cooperative Communications, Consensus, Diffusion, Spectrum Sensing, Cognitive Radio Sensor Networks (CRSNs), Link Failure.

9- Introduction and Patent Analysis of Signal Processing for Big Data

Book Chapter
Mohammad Eslami, Amirhosein Hajihoseini Gazestani and 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.

10- Image dataset for Persian Road Surface Markings

Conference paper
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.

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

Journal paper
Zahra Ezzati Khatab, Amirhosein Hajihoseini, 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.

Keywords:

Indoor localization, fingerprint, wireless sensor network, autoencoder, deep extreme learning machine

12- Distributed Spectrum Sensing for Cognitive Radio Sensor Networks using Diffusion Adaptation

Journal paper
Amirhosein Hajihoseini and Seyed Ali Ghorashi

Abstract:

Cognitive radio is a practical solution for spectrum scarcity. In cognitive networks, unlicensed (secondary) users should sense the spectrum before any usage, to make sure that the licensed (primary) users do not use the spectrum at that time. Due to the importance of spectrum sensing in cognitive networks, this should be fast and reliable, particularly in networks with communication link failure, which leads to network topology change. Decentralized decision making algorithms are known as a promising technique to provide reliability, scalability and adaptation, especially in sensor networks. In this paper, we propose a distributed diffusion based method in which, secondary users (sensors) cooperate to improve the performance of spectrum sensing. The proposed method provides a significant improvement in convergence rate and reliability. Simulation results indicate that the proposed algorithm shows an acceptable performance and converges twice faster than recently proposed consensus based spectrum sensing algorithms in the literature, and is almost insensitive to communication link failure.

Keywords:

Distributed, Consensus, Diffusion, Spectrum Sensing, Cognitive Radio Sensor Networks

13- Decentralized Consensus Based Target Localization in Wireless Sensor Networks

Journal paper
Amirhosein Hajihoseini, Reza Shahbazian and Seyed Ali Ghorashi

Abstract:

Target localization is an attractive subject for modern systems that utilize different types of distributed sensors for location based services such as navigation, public transport, retail services and so on. Target localization could be performed in both centralized and decentralized manner. Due to drawbacks of centralized systems such as security and reliability issues, decentralized systems are become more desirable. In this paper, we introduce a new decentralized and cooperative target localization algorithm for wireless sensor networks. In cooperative consensus based localization, each sensor knows its own location and estimates the targets position using the ranging techniques such as received signal strength. Then, all nodes cooperate with their neighbours and share their information to reach a consensus on targets location. In our proposed algorithm, we weight the received information of neighbour nodes according to their estimated distance toward the target node. Simulation results confirm that our proposed algorithm is faster, less sensitive to targets location and improves the localization accuracy by 85% in comparison with distributed Gauss–Newton algorithm.

Keywords

Wireless sensor network, Localization, Consensus, Weighted, Cooperative. 

14- موقعیت ‏یابی سه‏ بعدی درون ساختمانی با استفاده از سامانه ‏های مخابرات نور مرئی

Conference paper
امیرحسین حاجی حسینی، اکبر درگاهی، سیدعلی قرشی

چکیده

با توجه به افزایش استفاده از طیف فرکانسی و محدودیت ‏های طیفی، انتظار می‏رود مخابرات نوری به طور گسترده در سامانه ‏های جدید استفاده شود. مخابرات نور مرئی یکی از شاخه‏ هایی است که در سالیان اخیر مورد توجه قرار گرفته و یکی از مهم­ترین کاربردهای آن موقعیت ‏یابی درون ساختمانی است، زیرا درون ساختمان نمی‏توان به خوبی از سامانه موقعیت ‏یابی جهانی استفاده کرد و استفاده از سامانه ‏های نوری به عنوان جایگزین روش مناسبی است. در این مقاله یک روش برای موقعیت‏ یابی درون ساختمانی ارائه می‏شود که فقط به اتصال گیرنده و فرستنده ‏های نوری وابسته است. در این روش پیشنهادی با استفاده از پهنای میدان نوری، زاویه سیگنال دریافتی در گیرنده تخمین ‏زده می ­شود و با استفاده از تخمین ‏زننده حداقل مربعات، موقعیت گیرنده تعیین می ‏شود. نتایج شبیه ‏سازی­ ها نشان می ‏دهد که با استفاده از چهار دستگاه دسترسی نوری می‏ توان موقعیت یک گیرنده مخابرات نور مرئی را در یک فضای سه بعدی با خطایی در حدود 0.6 متر تخمین زد.

واژگان كليدي: موقعیت‏ یابی، مخابرات نور مرئی، تخمین‏ زننده‏ حداقل مربعات، مخابرات نوری.

15- Distributed Target Localization in Wireless Sensor Networks using Diffusion Adaptation

Journal paper
Amirhosein Hajihoseini, Seyed Ali Ghorashi

Abstract

Localization is an important issue for wireless sensor networks. Target localization has attracted many researchers who work on location based services such as navigation, public transportation and so on. Localization algorithms may be performed in a centralized or distributed manner. In this paper we apply diffusion strategy to the Gauss Newton method and introduce a new distributed diffusion based target localization algorithm for wireless sensor networks. In our proposed method, each node knows its own location and estimates the location of target using received signal strength. Then, all nodes cooperate with their neighbors and share their measurements to improve the accuracy of their decisions. In our proposed diffusion based algorithm, each node can localize target individually using its own and neighbor’s measurements, therefore, the power consumption decreases. Simulation results confirm that our proposed method improves the accuracy of target localization compared with alternative distributed consensus based target localization algorithms.  Our proposed algorithm is also shown that is robust against network topology and is insensitive to uncertainty of sensor nodes’ location.

Keywords: distributed; cooperative; target localization; wireless sensor network; Gauss Newton

16- مروری بر روش های موقعیت یابی در شبکه های حسگر بی سیم با استفاده ازالگوریتم های شناسایی آماری الگو

Conference paper
امیرحسین حاجی حسینی، رضا شهبازیان، سید علی قرشی، داوود غرویان

چیکیده:

استقرار یک سامانه ­ی موقعیت ­یابی برای گره ­های حسگر، یک مسئله ­ی اساسی برای بسیاری از کاربردها در شبکه ­های حسگر بی­ سیم است. از آنجا که ممکن است شبکه­ ی حسگر در منطقه­ ای غیرقابل دسترس مستقر شده باشد، ممکن است موقعیت حسگرها از قبل مشخص نباشد. بنابراین یک سامانه ­ی موقعیت­ یابی لازم است تا اطلاعات مکانی و موقعیت گره ­ها را در اختیار قرار دهد. در بسیاری از موارد قیمت و منابع محدود انرژی، اجازه ‏ي تجهیز تمامي حسگر­ها را به سامانه ‏ي موقعیت ­یابی جهانی نمی ­دهد. لذا روش­ هایی لازم است تا گره ­ها و حسگرها بتوانند موقعیت خود را در شبکه تخمین زنند. در این مقاله سعی داریم روش­ های مبتنی بر الگوریتم ­های شناسایی آماری الگو که در زمینه ­ی موقعیت ­یابی در شبکه ­ی حسگر بی ­سیم استفاده شده ­اند را معرفی و عملکرد آن­ها را مقایسه نماییم. با توجه به کاربردهای گسترده ­ای که الگوریتم­های شناسایی آماری الگو دارند، این مبحث در سال ­های اخیر توجه زیادی را در شاخه ­های مختلف علوم به خود جلب کرده است و می­تواند برای دسته ‏بندی اطلاعات و شناسایی الگوی آن ‏ها به کار رود.

کلمات کلیدی:

شبکه­های حسگر بی­سیم، موقعیت­ یابی، شناسایی آماری الگو، KNN، ماشین بردار پشتیبان، مدل مخفی مارکف.

این مقاله آبان 1394 در هجدهمین کنفرانس ملی دانشجویی مهندسی برق در مشهد ارائه و به عنوان مقاله برتر مخابرات سیستم انتخاب شد.