Hand-grip and body-loss impact on RSS measurements for localization of mass market devices

Rosa, Francescantonio Della; Xu, Li; Nurmi, Jari; Laoudias, Christos; Pelosi, Mauro; Terrezza, Amerigo

doi:10.1109/icl-gnss.2011.5955274

Cited by 24 publications

(21 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such signal attenuation due to human hands is referred to as hand-grip loss [7]. Various factors such as antenna position, area covered by the hand, and relative location of the hand can influence the hand-grip loss.…”

Section: B Handgrip Lossmentioning

confidence: 99%

“…In [7], the authors measure the hand-grip loss of several smartphones and utilize the loss to enhance the accuracy of localization of mobile devices in indoor environments. Inspired by [7], we measure the hand-grip loss of three widely used smartphones. Interestingly, we observe additional attenuation by the human face when the smartphone is brought near the face during phone call.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Toward realistic WiFi simulation with smartphone “Physics”

Yoo

Shin

Kim

et al. 2014

Proceeding of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks 2014

View full text Add to dashboard Cite

Various packet-based simulation tools (e.g., NS-3) have been employed for design, validation, and evaluation of new protocols for WiFi networks since they offer cost efficiency, scalability, and reproducibility. These benefits come, however, at the expense of lack of realism compared to live testbed experiments. This is attributed in a major part to the difficulty of capturing detailed characteristics of channel dynamics, bit-level protocol specification (PHY layer), and application/user behaviors in a high-fidelity manner. The performance gap predicted by simulation and live testbed becomes even more pronounced when one considers a wide diversity of device characteristics and the way each device is used by end users. For example, smartphones generally show worse WiFi performance than other WiFi devices (e.g., laptops and tablets) because smartphones suffer from additional signal loss due to hand-grips and the low antenna gains of their embedded antennas. The goal of this study is to significantly close the gap by incorporating survey-and measurement-based smartphone WiFi characteristics and realistic hand-grip models into traditional WiFi network simulators (NS-3 in this study). The enhanced WiFi simulation tool's performance prediction capability is validated through an comparative study between testbed experiments and simulations.

show abstract

Section: B Handgrip Lossmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Toward realistic WiFi simulation with smartphone “Physics”

Yoo

Shin

Kim

et al. 2014

Proceeding of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks 2014

View full text Add to dashboard Cite

show abstract

“…All phones used during the test were of an exact make and model so as to rule out any issues with varied RSSI reads with different antenna types. Some of these issues have been described in the literature [18,19]. Lisheng et al, [19] go so far as to describe the distortion being as much as 11.2 dBm out with different antenna types over a 25 meter read range.…”

Section: A System Componentsmentioning

confidence: 99%

“…During the tests all phones were placed at a distance of 80cm above floor level, to mimic as close to a real world example of a user holding them. The phones were placed on identical platforms during the tests to negate the impact of Hand-Grip body-loss effect which can also impact ranging measurements [18]. Device orientation can also introduce errors when calculating signal range estimates, so all phones had the same orientation when used in our tests [20].…”

Section: A System Componentsmentioning

confidence: 99%

To wireless fidelity and beyond — CAPTURE, extending indoor positioning systems

Cullen

Curran

Santos

et al. 2014

2014 Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS)

View full text Add to dashboard Cite

Most of the current research into indoor localization has surrounded the problem of positioning accuracy, with attempts to solve this using a myriad of technologies and algorithms. One of the problems that seems to be somewhat overlooked is the issue of coverage in an indoor localization solution. The mostly unobstructed views of the Global Positioning System (GPS) which requires a mere 30 satellites to provide global coverage never had these problems. Unfortunately unobstructed views are not something that can be achieved in most indoor environments and economical as well as physical barriers can prevent the installation of an infrastructure to achieve total coverage. In this paper we propose a solution to this issue of indoor coverage by deploying a solution to extend the range of a positioning system -Cooperatively Applied Positioning Techniques Utilizing Range Extension (CAPTURE). CAPTURE provides a system to locate devices that cannot be reached by an in-house location based system. It presents a unique contribution to research in this field by offering the ability to utilize devices that currently know their location within a Location Based Solution (LBS), to help evaluate the position of unknown devices beyond the range capacity of the LBS. Effectively extending the locating distances of an Indoor LBS by utilizing the existing mobile infrastructure without the requirement for additional hardware. CAPTURE uses the Bluetooth radios on mobile devices to estimate the distance between devices, before inserting these range estimates into a trilateration algorithm to ascertain position. CAPTURE has been tested through experiments carried out in a real world environment, proving the capacity to provide a solution to the ranging issue.

show abstract

“…Second, if the lineof-sight (LOS) between the AP and the device is obstructed by the body, there is additional loss. The body loss parameters depends on the device used and the user grip [18]. For this research, the body loss parameters were estimated from experiment using an LG optimus1 P500 mobile device.…”

Section: Body Loss Modelmentioning

confidence: 99%

Wilocsim: Simulation Testbed for Wlan Location Fingerprinting Systems

Sapumohotti¹,

Alias²,

Tan³

2013

PIER B

View full text Add to dashboard Cite

Abstract-This paper introduces a novel simulation testbed for investigating WLAN indoor localization systems. This testbed referred to as WiLocSim consists of a novel beacon received signal strength (RSS) simulator which provides realistic modeling of beacon signal characteristics such as multipath propagation, measurement noise and body loss. Each component of the simulator is individually modeled and verified prior to integration. In addition, the capabilities of the testbed are demonstrated using two variants of the nearest neighbor classification based indoor localization algorithm. Unlike conventional measurement based performance evaluation, the proposed testbed provides a reproducible environment for accurate evaluation and analysis of indoor localization systems. More importantly, it significantly reduces the high labor cost typically required in measurement based testbed.

show abstract

Hand-grip and body-loss impact on RSS measurements for localization of mass market devices

Cited by 24 publications

References 18 publications

Toward realistic WiFi simulation with smartphone “Physics”

Toward realistic WiFi simulation with smartphone “Physics”

To wireless fidelity and beyond — CAPTURE, extending indoor positioning systems

Wilocsim: Simulation Testbed for Wlan Location Fingerprinting Systems

Contact Info

Product

Resources

About

Hand-grip and body-loss impact on RSS measurements for localization of mass market devices

Cited by 24 publications

References 18 publications

Toward realistic WiFi simulation with smartphone &#x201C;Physics&#x201D;

Toward realistic WiFi simulation with smartphone &#x201C;Physics&#x201D;

To wireless fidelity and beyond &#x2014; CAPTURE, extending indoor positioning systems

Wilocsim: Simulation Testbed for Wlan Location Fingerprinting Systems

Contact Info

Product

Resources

About

Toward realistic WiFi simulation with smartphone “Physics”

Toward realistic WiFi simulation with smartphone “Physics”

To wireless fidelity and beyond — CAPTURE, extending indoor positioning systems