Title

Closed-Form Path-Loss Predictor for Gaussianly Distributed Nodes

Document Type

Conference Proceeding

Publication Date

5-23-2010

Keywords

stochastic geometry, Monte Carlo simulation, spatial distribution, cellular communication, statistical modeling, statistical analysis, mobile radio, network geometry, cellular radio, mobile communication, path loss, gaussian distribution, network deployment

Abstract

The emulation of wireless nodes spatial position is a practice used by deployment engineers and network planners to analyze the characteristics of a network. In particular, nodes geo-location will directly impact factors such as connectivity, signals fidelity, and service quality. In literature, in addition to typical homogeneous scattering, normal distribution is frequently used to model mobiles concentration in a cellular system. Moreover, Gaussian dropping is often considered as an effective placement method for airborne sensor deployment. Despite the practicality of this model, getting the network channel loss distribution still relies on exhaustive Monte Carlo simulation. In this paper, we argue the need for this inefficient approach and hence derived a generic and exact closed-form expression for the path-loss distribution density between a base-station and a network of nodes. Simulation was used to reaffirm the validity of the theoretical analysis using values from the new IEEE 802.20 standard.

Faculty

Faculty of Applied Science and Technology (FAST)

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Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

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