A simple and efficient model for indoor path-loss prediction

Pérez‐Vega, C.; G, Jose Luis García; Higuera, José Miguel López

doi:10.1088/0957-0233/8/10/020

Cited by 13 publications

(5 citation statements)

References 14 publications

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“…where G ij is the path gain 1 which is modeled as proportional to the attenuation factor d −β ij [13] where d ij is the pair distance between node i and j, and β is the pathloss exponent [7]. The antenna gain and coding gain are also assumed to be included in G ij .…”

Section: B Received Signalmentioning

confidence: 99%

Optimal Cross-Tier Power Allocation for D2D Multi-Cell Networks

Tang

Coon

Chen

2016

2016 IEEE Global Communications Conference (GLOBECOM)

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Efficient transmission power control is indispensable for cellular networks. It not only provides a high energy efficiency, but also maintains reliable connections. With the emergence of 5G mobile technology, the presence of device-to-device (D2D) communications within the cellular network has stimulated research on radio resource sharing. In this paper, we consider an underlay D2D network operating in a Rayleigh fading channel and propose a power allocation method that assigns transmit power levels to D2D UEs (DUEs) and cellular UEs (CUEs) such that the joint connection probability of DUEs and CUEs is maximized. The approach is formulated as a optimization problem, and we prove that the problem is log concave. Hence, the optimum powers for active UEs can be found easily using modern computational methods. Both the theoretical and simulated results show that the joint connectivity probability is improved by one to two orders of magnitude by applying the optimization procedure compared to conventional LTE open loop power allocation. This dramatic improvement comes at the cost of an increase in UE average transmit power. Thus, the proposed technique is well suited to 5G public safety and disaster relief communication modes where enhanced connectivity is the top priority.

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Section: B Received Signalmentioning

confidence: 99%

Optimal Cross-Tier Power Allocation for D2D Multi-Cell Networks

Tang

Coon

Chen

2016

2016 IEEE Global Communications Conference (GLOBECOM)

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“…Free-space path loss is defined as the loss in signal strength in free space (air). The indoor path loss equation estimates the path loss inside a room or closed-in area inside a building that is surrounded by walls [21]. Eqn.…”

Section: Proposed Man-in-the-middle Detection Methodsmentioning

confidence: 99%

“…Eqn. 1 is a standard indoor path loss function, which requires a number of variables in order to determine the path loss [21].…”

Section: Proposed Man-in-the-middle Detection Methodsmentioning

confidence: 99%

Detecting and Locating Man-in-the-Middle Attacks in Fixed Wireless Networks

Dong

Espejo

Wan

et al. 2015

CIT

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We propose a novel method to detect and locate a Man-in-the-Middle attack in a fixed wireless network by analyzing round-trip time and measured received signal strength from fixed access points. The proposed method was implemented as a client-side application that establishes a baseline for measured round trip time (RTTs) and received signal strength (RSS) under no-threat scenarios and applies statistical measures on the measured RTT and RSS to detect and locate Man-in-the-Middle attacks. We show empirically that the presence of a Man-in-the-Middle attack incurs a significantly longer delay and larger standard deviation in measured RTT compared to that measured without a Man-in-the-Middle attack. We evaluated three machine learning algorithms on the measured RSS dataset to estimate the location of a Man-in-the-Middle attacker. Experimental results show that the proposed method can effectively detect and locate a Man-in-the-Middle attack and achieves a mean location estimation error of 0.8 meters in an indoor densely populated metropolitan environment.

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“…Table I lists the RF propagation parameters of interest at 500, 1000 and 2000 MHz: (i) the offset, i.e., the loss at d 0 = 1 meter from the transmitting antenna [10]; (ii) the path loss exponent (attenuation slope) inside a typical office building [10]; (iii) the attenuation factor (specific attenuation) through concrete [11]. The path loss exponent outside the building (β slope,out ) was assumed to be 20 dB/decade [12]. Table I indicates that the through-wall attenuation is more than 10 dB lower at 1 GHz than at 2 GHz.…”

Section: E Sinogram Acquisitionmentioning

confidence: 99%

Evaluation of RF Through-The-Wall Mapping Reconstruction Methods using an Objective Image Quality Index

Campos¹,

Lovisolo²,

Campos³

2019

Anais De XXXVII Simpósio Brasileiro De Telecomunicações E Processamento De Sinais

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This work aims at comparing four reconstruction techniques (Filtered Backprojection Reconstruction, Direct Fourier Reconstruction, Algebraic Reconstruction Technique and Simultaneous Iterative Reconstruction Technique) that can be applied to RF-based through-the-wall mapping. All these methods were originally used in computerized X-ray tomography. A stochastic simulation model is set up, using pathloss equations corrupted by Rayleigh noise to account for multipath reception of the RF wave and two test floor maps are defined. From that analysis, a metric for image quality assessment (Mean Structural Similarity Index) is selected to allow an objective comparison of the reconstructed images.

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A simple and efficient model for indoor path-loss prediction

Cited by 13 publications

References 14 publications

Optimal Cross-Tier Power Allocation for D2D Multi-Cell Networks

Optimal Cross-Tier Power Allocation for D2D Multi-Cell Networks

Detecting and Locating Man-in-the-Middle Attacks in Fixed Wireless Networks

Evaluation of RF Through-The-Wall Mapping Reconstruction Methods using an Objective Image Quality Index

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