NDLI: The probability distribution of the carrier-to-interference ratio (CIR) of a CSMA/CA ad hoc wireless network

Content Provider	IEEE Xplore Digital Library
Author	Qasmi, S.A. Wong, K.T.
Copyright Year	2005
Description	Author affiliation: Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont. (Qasmi, S.A.; Wong, K.T.)
Abstract	This work is first in the open literature to characterize the probability distribution (not merely the mean and variance) of the carrier-to-interference ratio (CIR) of an ad hoc CSMA/CA wireless communication network, via Monte Carlo simulations. This paper is also first in the open literature to model an ad hoc network accounting for all following factors: (1) more realistically modeling of the network nodes' spatial distribution via a two-dimensional Poisson process whereby network nodes are randomly placed at arbitrary two-dimensional plane (instead of nodes locating deterministically at only regular grid points), (2) suppression of nodes within the carrier sensing range of a transmitting node to micmac the CSMA/CA medium access control (MAC) protocol (i.e. nodes self-restrain from transmission when neighboring a transmitting node), (3) microscopic Rayleigh fading, (4) propagation-distance-dependent path-loss and (5) more than one service class. Monte Carlo simulations of a CSMA/CA ad hoc network generate CIR data, whose probability distribution function and parameters are identified via least-squares curve-fitting. The inverse normal distribution is the most well-rounded distribution, in the sense of providing a good fit (if not the best fit) to all nine Monte-Carlo simulation scenarios. The Rayleigh is the best univariate pdf. It can fit all scenarios very well, except the case without micro-fading and low pathless. All pdf's can sufficiently fit the data when k=4 Nakagami is the best bivariate pdf with LMSE les1, except the case without micro-fading and low-pathloss (with distance-dependent power-loss exponent k=2). The bivariate Nakagami improves over the best univariate fit (namely, Rayleigh). The trivariate Fisk & quadravariate Burr can fit all scenarios with LMSE les 1. The quadravariate Burr often cuts the trivariate Fisks LMSE by half. The trivariate Fisk cuts the bivariate inverted-normals LMSE often by 2/3
Starting Page	996
Ending Page	1001
File Size	2857944
Page Count	6
File Format	PDF
ISBN	0780393937
DOI	10.1109/MILCOM.2005.1605809
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Probability distribution Multiaccess communication Wireless networks Ad hoc networks Media Access Protocol Wireless communication Access protocols Microscopy Rayleigh channels Curve fitting
Content Type	Text
Resource Type	Article

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