Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.2
3.0
Journals
Energies
Special Issues
Wireless Communication Systems for Localization
energies-logo
Submit to Energies Review for Energies Propose a Special Issue

Journal Menu

► Journal Menu

Journal Browser

► Journal Browser
share announcement

Wireless Communication Systems for Localization

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F: Electrical Engineering".

Deadline for manuscript submissions: closed (31 August 2019) | Viewed by 26127

Special Issue Editor

Prof. Dr. Suk-Seung Hwang

E-Mail
Guest Editor
Department of Electronic Engineering, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 501-759, Republic of Korea
Interests: adaptive signal processing; wireless communications; location detection technology; interference cancellation; channel estimation; GPS; RFID
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Location detection technology (LDT), which has a variety of applications, including the energy consumption monitoring system, is one of core techniques in modern wireless communication systems. As wireless communication techniques are developed, we can find more and more applications related to LDT in industrial fields. Many researchers involved in this area are pushing to efficiently develop accurate mobile devices with high performance, low-costs, and reusability of components.

The goal of this Special Issue is to contribute to the development of various theories, applications, mathematical models, simulations, etc., related to localization techniques based on wireless communication systems.

Topics of interest include, but are not limited to:

  • Advanced Location Detection Technologies Related to Time of Arrival (ToA), Time Difference of Arrival (TDoA), Angle of Arrival (AoA), Cell ID, Fingerprinting Technique, Trilateration, etc.
  • Localization in Networks (IoT, Next Generation, Vehicle, ITS, etc.)
  • Indoor Localization and RFID Based Positioning Technique
  • Localization for Energy Saving and Energy Management
  • Signal Processing and Communication Theory for Localization
  • Statistical and Adaptive Signal Processing for Localization
  • Location-Based-Service Applications Including Emergency Service
  • Localization Technique for Disaster
  • Satellite Based Positioning Technique (Global Positioning System, Galileo, COMPASS, GLONASS, etc.)
  • Maritime and Underwater Localization
  • AOA Estimation and Ranging Techniques

Prof. Dr. Suk-Seung Hwang
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • localization
  • location detection technology
  • wireless communications
  • satellite based positioning
  • indoor positioning
  • networks
  • energy saving
  • energy management
  • location-based-service
  • signal processing
  • adaptive signal processing
  • angle of arrival estimation
  • ranging technique
  • underwater localization

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue polices can be found here.

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

30 pages, 3200 KiB  
Article
Secure Routing Protocols for Source Node Privacy Protection in Multi-Hop Communication Wireless Networks
by Lilian C. Mutalemwa and Seokjoo Shin
Energies 2020, 13(2), 292; https://doi.org/10.3390/en13020292 - 7 Jan 2020
Cited by 23 | Viewed by 2667
Abstract
Traffic analysis attacks are common in monitoring wireless sensor networks (WSNs). In the attacks, adversaries analyze the traffic pattern to obtain critical information such as the location information of a source node. Fake source packet routing protocols are often used to ensure source [...] Read more.
Traffic analysis attacks are common in monitoring wireless sensor networks (WSNs). In the attacks, adversaries analyze the traffic pattern to obtain critical information such as the location information of a source node. Fake source packet routing protocols are often used to ensure source location privacy (SLP) protection. The protocols rely on broadcasting fake packets from fake sources concurrently with the transmission of real packets from the real source nodes to obfuscate the adversaries. However, fake source packet routing protocols have demonstrated some performance limitations including high energy consumption, low packet delivery ratio (PDR), and long end-to-end delay (EED). In this study, two existing fake source packet routing protocols are considered. Then two new phantom-based SLP routing protocols are proposed to address the limitations. Each proposed protocol introduces a two-level phantom routing strategy to ensure two adversary confusion phases. When the adversaries perform traffic analysis attacks on the packet routes, they encounter two levels of obfuscation. Simulation results establish that the proposed protocols have superior performance features. The protocols guarantee strong SLP protection throughout the WSN domain with controlled energy consumption, PDR, and EED. Furthermore, the proposed protocols achieve more practical results under varied network configurations. Full article
(This article belongs to the Special Issue Wireless Communication Systems for Localization)
►▼ Show Figures

Graphical abstract

20 pages, 4011 KiB  
Article
A Smartphone Indoor Positioning System Using Hybrid Localization Technology
by Hui-Seon Gang and Jae-Young Pyun
Energies 2019, 12(19), 3702; https://doi.org/10.3390/en12193702 - 27 Sep 2019
Cited by 25 | Viewed by 4907
Abstract
As smartphone built-in sensors, wireless technologies, and processor computing power become more advanced and global positioning system (GPS)-based positioning technologies are improving, location-based services (LBS) have become a part of our daily lives. At the same time, demand has grown for LBS applications [...] Read more.
As smartphone built-in sensors, wireless technologies, and processor computing power become more advanced and global positioning system (GPS)-based positioning technologies are improving, location-based services (LBS) have become a part of our daily lives. At the same time, demand has grown for LBS applications in indoor environments, such as indoor path finding and navigation, marketing, entertainment, and location-based information retrieval. In this paper, we demonstrate the design and implementation of a smartphone-based indoor LBS system for location services consisting of smartphone applications and a server. The proposed indoor LBS system uses hybrid indoor positioning methods based on Bluetooth beacons, Geomagnetic field, Inertial Measurement Unit (IMU) sensors, and smartphone cameras and can be used for three types of indoor LBS applications. The performance of each positioning method demonstrates that our system retains the desired accuracy under experimental conditions. As these results illustrate that our system can maintain positioning accuracy to within 2 m 80% of the time, we believe our system can be a real solution for various indoor positioning service needs. Full article
(This article belongs to the Special Issue Wireless Communication Systems for Localization)
►▼ Show Figures

Graphical abstract

10 pages, 1783 KiB  
Article
DNN-Assisted Cooperative Localization in Vehicular Networks
by Jewon Eom, Hyowon Kim, Sang Hyun Lee and Sunwoo Kim
Energies 2019, 12(14), 2758; https://doi.org/10.3390/en12142758 - 18 Jul 2019
Cited by 13 | Viewed by 3312
Abstract
This work develops a deep-learning-based cooperative localization technique for high localization accuracy and real-time operation in vehicular networks. In cooperative localization, the noisy observation of the pairwise distance and the angle between vehicles causes nonlinear optimization problems. To handle such a nonlinear optimization [...] Read more.
This work develops a deep-learning-based cooperative localization technique for high localization accuracy and real-time operation in vehicular networks. In cooperative localization, the noisy observation of the pairwise distance and the angle between vehicles causes nonlinear optimization problems. To handle such a nonlinear optimization task at each vehicle, a deep neural network (DNN) technique is to replace a cumbersome solution of nonlinear optimization along with the saving of the computational loads. Simulation results demonstrate that the proposed technique attains some performance gain in localization accuracy and computational complexity as compared to existing cooperative localization techniques. Full article
(This article belongs to the Special Issue Wireless Communication Systems for Localization)
►▼ Show Figures

Graphical abstract

18 pages, 7674 KiB  
Article
Robust Localization for Robot and IoT Using RSSI
by Youngchul Bae
Energies 2019, 12(11), 2212; https://doi.org/10.3390/en12112212 - 11 Jun 2019
Cited by 20 | Viewed by 4409
Abstract
Node-localization technology has been supported in the wireless sensor network (WSN) environment. Node localization is based on a few access-point (AP) nodes that comprises positioning information because they are fixed, and a beacon node that comprises unknown positioning information because it is moving. [...] Read more.
Node-localization technology has been supported in the wireless sensor network (WSN) environment. Node localization is based on a few access-point (AP) nodes that comprises positioning information because they are fixed, and a beacon node that comprises unknown positioning information because it is moving. To determine the position of the unknown node, it must use two or three APs that comprise certain positioning information. There are a number of representative range-based methods, including time of arrival (TOA), weighted centroid locating algorithm, received signal strength intensity (RSSI), and time difference of arrival (TDOA) signal, that are received by the receiver. The RSSI method has its advantages. A simple device structure means that the RSSI method is easy to use. Because the structures of previous wireless local area network (LAN) technologies make them compatible with RSSI information, the RSSI method is widely used in the related area of position tracking. In addition, this algorithm has a hardware system that cannot be increased, has the advantage of the miniaturization of the node, and can wear through obstacles. This paper proposes the application of a robust ranging method that can be applied in robots and Internet of Things (IoT) using RSSI, especially in the tracing location of each nursing home patient, where the RSSI method with trilateral technique is used. This paper shows the results of the measured point from the application of the trilateral technique, and it also represents the results of the error distance between the ideal point and the measured point using computer simulation. Finally, this paper presents an estimation of localization using a real experimental device with a BLE (Bluetooth low-energy) transmitter and receiver, and beacon gateway, by applying an RSSI algorithm with the trilateral technique. Full article
(This article belongs to the Special Issue Wireless Communication Systems for Localization)
►▼ Show Figures

Figure 1

26 pages, 4245 KiB  
Article
Hybrid TOA Trilateration Algorithm Based on Line Intersection and Comparison Approach of Intersection Distances
by Sajina Pradhan, Youngchul Bae, Jae-Young Pyun, Nak Yong Ko and Suk-seung Hwang
Energies 2019, 12(9), 1668; https://doi.org/10.3390/en12091668 - 1 May 2019
Cited by 11 | Viewed by 3453
Abstract
The ever-growing mobile station (MS) localization technologies provide an increasingly important role in all aspects of the wireless cellular systems and Internet of Things (IoT). The accurate MS location information is the basis in connection of different devices in IoT. The MS localization [...] Read more.
The ever-growing mobile station (MS) localization technologies provide an increasingly important role in all aspects of the wireless cellular systems and Internet of Things (IoT). The accurate MS location information is the basis in connection of different devices in IoT. The MS localization techniques based on time of arrival (TOA) trilateration algorithm, which determines the location of MS using an intersection point of three circles based on distances between MS and base stations (BS) and coordinates of BSs, have been actively studied. In general, the distance between the MS and BS is calculated by counting the number of delay samples or measuring the power of the received signal. Since the estimated distance (radius of a circle) between MS and BS is commonly increased, three circles may not meet at a single point, resulting in the estimation error of MS localization. In order to improve this problem, in this paper, we propose the hybrid TOA trilateration algorithm based on the line intersection algorithm for the general case for intersection of three circles and the comparison approach of intersection distances for the specific case where a small circle is located inside the area of two large circles. The line intersection algorithm has an excellent location estimation performance in the general case, but it does not work in the specific case. The comparison approach of intersection distances has good performance only for the specific case. In addition, we propose the mode selection algorithm to efficiently select a proper mode between the general and specific cases. The representative computer simulation examples are provided to verify the localization performance of the proposed algorithm. Full article
(This article belongs to the Special Issue Wireless Communication Systems for Localization)
►▼ Show Figures

Figure 1

32 pages, 7325 KiB  
Article
Accurate Fall Detection and Localization for Elderly People Based on Neural Network and Energy-Efficient Wireless Sensor Network
by Sadik Kamel Gharghan, Saleem Latteef Mohammed, Ali Al-Naji, Mahmood Jawad Abu-AlShaeer, Haider Mahmood Jawad, Aqeel Mahmood Jawad and Javaan Chahl
Energies 2018, 11(11), 2866; https://doi.org/10.3390/en11112866 - 23 Oct 2018
Cited by 54 | Viewed by 6548
Abstract
Falls are the main source of injury for elderly patients with epilepsy and Parkinson’s disease. Elderly people who carry battery powered health monitoring systems can move unhindered from one place to another according to their activities, thus improving their quality of life. This [...] Read more.
Falls are the main source of injury for elderly patients with epilepsy and Parkinson’s disease. Elderly people who carry battery powered health monitoring systems can move unhindered from one place to another according to their activities, thus improving their quality of life. This paper aims to detect when an elderly individual falls and to provide accurate location of the incident while the individual is moving in indoor environments such as in houses, medical health care centers, and hospitals. Fall detection is accurately determined based on a proposed sensor-based fall detection algorithm, whereas the localization of the elderly person is determined based on an artificial neural network (ANN). In addition, the power consumption of the fall detection system (FDS) is minimized based on a data-driven algorithm. Results show that an elderly fall can be detected with accuracy levels of 100% and 92.5% for line-of-sight (LOS) and non-line-of-sight (NLOS) environments, respectively. In addition, elderly indoor localization error is improved with a mean absolute error of 0.0094 and 0.0454 m for LOS and NLOS, respectively, after the application of the ANN optimization technique. Moreover, the battery life of the FDS is improved relative to conventional implementation due to reduced computational effort. The proposed FDS outperforms existing systems in terms of fall detection accuracy, localization errors, and power consumption. Full article
(This article belongs to the Special Issue Wireless Communication Systems for Localization)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop