A new statistical model for site-specific indoor radio propagation prediction based on geometric optics and geometric probability

Hassan-Ali, M.; Pahlavan, Kaveh

doi:10.1109/7693.975450

Cited by 111 publications

(59 citation statements)

References 17 publications

(36 reference statements)

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“…Also, the reflection coefficients are very small when the incident radio wave reflects on the floor or the ceiling [18], thereby leading to predominantly azimuthal signal propagation. Therefore, the current work considers only two-dimensional (2-D) propagation in line with other existing indoor channel models [8,9,16,18,21,22]). …”

Section: Introductionmentioning

confidence: 99%

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Geometry-Based Statistical Model for Radio Propagation in Rectangular Office Buildings

Chen¹,

Zhang²,

Hu³

et al. 2009

PIER B

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Abstract-We present a new approach to the modeling of angle and time of arrival statistics for radio propagation in typical office buildings, in which the majority of interior scattering objects are either parallel or perpendicular to the exterior walls. We first describe the reradiating elements in office buildings as randomly distributed arrays of thin strips. The amount of clutter and the amount of transmission/reflection loss are then accounted for through several key parameters of the site-specific features of indoor environment, such as the layout and materials of the building under consideration. Subsequently, the important channel parameters including power azimuthal spectrum (PAS) and power delay spectrum (PDS) are derived. An appealing observation is that when the path angles from multiple channel trials are measured and collectively analyzed, deterministic angle clustering becomes evident. This phenomenon agrees well with the existing ray-tracing (RT) results reported by Jo et al. in buildings of this type and cannot be explained by other geometric channel models (GCMs). Furthermore, the proposed model predicts an asymmetric cluster PAS for a single-channel-trial scenario, which yields an excellent fit to the experimental data presented by Poon and Ho. Finally, we have also investigated the behaviors of the superimposed PAS and PDS under various channel conditions.

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Section: Introductionmentioning

confidence: 99%

“…Then all the possible paths connecting the transmitter (Tx) and the receiver (Rx) are found through the specified complicated environment. Fast RT techniques have been intensively pursued in recent years to expedite the computation time [16,17].…”

Section: Introductionmentioning

confidence: 99%

Geometry-Based Statistical Model for Radio Propagation in Rectangular Office Buildings

Chen¹,

Zhang²,

Hu³

et al. 2009

PIER B

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“…This model is demonstrated by a Monte Carlo simulation [7]. Thus, substituting (7) and (8) in (6), the final path loss equation for the multi-path is determined as below.…”

Section: -1 Site-specific Path Loss Model Based On Geometricmentioning

confidence: 99%

“…Optics and Geometric Probability [7] When the transmitting power from transmitter (Tx) is radiated and arrived at a receiving point (Rx), the propagating rays experience many reflections and transmissions due to object-intersections. Consequently, the path power tends to decay rapidly with distance at a rate more than the inverse-square distance law for the free-space.…”

Section: -1 Site-specific Path Loss Model Based On Geometricmentioning

confidence: 99%

An Interference Analysis Method with Site-Specific Path Loss Model for Wireless Personal Area Network

Moon¹,

Kwon²,

Lee³

et al. 2010

Journal of electromagnetic engineering and science

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In this paper, an interference analysis method with a site-specific path loss model for a wireless personal area network (WPAN) is proposed. The site-specific path loss model is based on geometrical optics and geometric probability to consider both site-specific radio propagation characteristics and a closed-form expression to obtain the mean interference from which the uniformly distributed multiple interferers are derived. Therefore, the proposed interference analysis method can achieve more computational simplicity than the Monte-Carlo (MC) simulation, which uses the ray-tracing (RT) technique. In addition, better accuracy than the conventional interference analysis model that uses stochastic method can also be achieved. To evaluate the proposed method, a signal to the interference-noise ratio with a mean interference concept for uniformly distributed interferers is calculated and compared in two simulation scenarios. As a result, the proposed method produces not only better matched results with the MC simulation using the RT technique than the conventional interference analysis model, but also simpler and faster calculation, which is due to the site-specific path loss model and closed-form expression for interference calculation. Ⅰ. IntroductionAs the demand for wireless communication services for indoor environments to provide multi-function and high data rate increase, more and more electrical devices short-range radio interfaces such as ultra-wideband (UWB), Zigbee, and Bluetooth are developed. These wireless communication technologies are standardized in the IEEE 802. 15 task group for wireless personal area networks (WPAN) [1]. In addition, a wireless sensor network is composed by these applications for each service target. However, because these applications generally utilize common unlicensed industrial, scientific, and medical (ISM) bands, they have difficulty in controlling the co- Fig. 1. Geometry of interference model. mmunication services for multi-users. Therefore, these applications can interfere with each other because they tend to be located in close proximity. In addition, UWB techniques, which are considered a means of supporting a high data rate, reuse the existing radio spectrum so that UWB systems can generate interference with other radio communication systems. For these reasons, many studies on the coexistence of different communication systems in WPAN applications or wireless local area network (W-LAN) applications have been done [2～4].The methods of analyzing interference effects are categorized into minimum coupling loss (MCL), enhanced MCL (E-MCL), and the Monte-Carlo (MC) based method. The E-MCL method is also known as the stochastic method; it assumes that interferers are uniformly distributed in an interference zone as shown in Fig. 1. In this method, the path loss is calculated by the simple and empirical path loss model with path loss exponents for indoor environments. Conventional interference analysis is performed mainly by this stochastic method. Although this meth...

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“…First suggested by Bahl et al [3], this technique uses the triangulation of a client's received signal strength from multiple perspectives and compares them against a map of known signal strength readings to determine their location. Because such static maps fail to capture the dynamic nature of signal strength and are time-intensive to create, a number of modifications including statistical modeling [13] and the automatic generation [14], [15] and calibration of maps [16] were used to extend this basic technique. Faria et al [10] use overprovisioning and access-point specific handshakes to provide localization; however, this approach is not robust against a single direct antenna.…”

Section: Related Workmentioning

confidence: 99%

Constructing Secure Localization Systems with Adjustable Granularity Using Commodity Hardware

Traynor

Schiffman

Porta

et al. 2010

2010 IEEE Global Telecommunications Conference GLOBECOM 2010

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Abstract-Proof of a user's identity is not always a sufficient means for making an authorization decision. In an increasing set of circumstances, knowledge of physical location provides additional and necessary context for making decisions about resource access. For example, sensitive information stored on a laptop (e.g. customer records, social security numbers, etc), may require additional protections if a user operates outside of an approved area. However, current localization techniques based on signal strength reporting or specialized hardware fail to achieve this goal. In this paper, we design, develop, deploy and measure a system which securely determines the location of a user to within one meter through using only off-the-shelf 802.11 and Bluetooth equipment. We apply this equipment in a two-phased challengeresponse protocol: first determining the general area of the client in the Regionalization phase and then pinpointing it in the Localization phase. Using nearly 32,000 data points collected over 75 days, we argue that the stability of wireless networks over time creates easily distinguishable location profiles by which a client can be positioned. Additionally, we demonstrate the inherent ability of a two-phased protocol to discern a client's location information at a level of granularity no finer than is necessitated by policy. After discussing a number of applications, we build a location-based access control framework that automatically protects a white-listed set of resources through encryption when the user leaves specified areas. Our analyses show that this system provides a realistic and efficient means of incorporating unforgeable location information at the appropriate level of granularity into many authorization decisions.

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A new statistical model for site-specific indoor radio propagation prediction based on geometric optics and geometric probability

Cited by 111 publications

References 17 publications

Geometry-Based Statistical Model for Radio Propagation in Rectangular Office Buildings

Geometry-Based Statistical Model for Radio Propagation in Rectangular Office Buildings

An Interference Analysis Method with Site-Specific Path Loss Model for Wireless Personal Area Network

Constructing Secure Localization Systems with Adjustable Granularity Using Commodity Hardware

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