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Outage probability scaling laws for SISO and MIMO ad‐hoc networks
Author(s) -
Keshavarz Hengameh,
AhmadiShokouh Javad
Publication year - 2013
Publication title -
transactions on emerging telecommunications technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.366
H-Index - 47
ISSN - 2161-3915
DOI - 10.1002/ett.2542
Subject(s) - wireless ad hoc network , bounded function , independent and identically distributed random variables , topology (electrical circuits) , node (physics) , probability density function , fading , upper and lower bounds , random variable , gaussian , coverage probability , stochastic geometry models of wireless networks , computer science , channel (broadcasting) , probability distribution , mathematics , optimized link state routing protocol , computer network , statistics , telecommunications , wireless , combinatorics , physics , mathematical analysis , confidence interval , quantum mechanics
In this paper, the outage probability scaling laws for ad‐hoc networks with an arbitrary topology is studied. In single‐input single‐output ad‐hoc networks, the outage probability is tightly bounded as the number of users goes to infinity in case that channel gains are independent and identically distributed (i.i.d.). If channel gains are not i.i.d. or calculating the distribution function is complicated because path loss, it is still possible to bound the outage probability if the distances between transmitter–receiver pairs are bounded. However, there is a gap between the upper and lower bounds. Unlike previous results, our analysis is completely general and is not limited to specific node and fading distributions. In multiple‐input multiple‐output ad‐hoc networks, the calculations are much more complicated, and it is hard to tightly bound the outage probability. For a special case of i.i.d. Gaussian channel matrices, the outage probability is asymptotically bounded in terms of Chi‐square distribution functions. Finally, as an application, the outage probability analysis is utilized to study delay scaling laws in random ad‐hoc networks. Simulation results show accuracy of this estimation for different scenarios. Copyright © 2012 John Wiley & Sons, Ltd.