7,379 research outputs found
What is the best spatial distribution to model base station density? A deep dive into two european mobile networks
This paper studies the base station (BS) spatial distributions across different scenarios in urban, rural, and coastal zones, based on real BS deployment data sets obtained from two European countries (i.e., Italy and Croatia). Basically, this paper takes into account different representative statistical distributions to characterize the probability density function of the BS spatial density, including Poisson, generalized Pareto, Weibull, lognormal, and \alpha -Stable. Based on a thorough comparison with real data sets, our results clearly assess that the \alpha -Stable distribution is the most accurate one among the other candidates in urban scenarios. This finding is confirmed across different sample area sizes, operators, and cellular technologies (GSM/UMTS/LTE). On the other hand, the lognormal and Weibull distributions tend to fit better the real ones in rural and coastal scenarios. We believe that the results of this paper can be exploited to derive fruitful guidelines for BS deployment in a cellular network design, providing various network performance metrics, such as coverage probability, transmission success probability, throughput, and delay
Matching theory for priority-based cell association in the downlink of wireless small cell networks
The deployment of small cells, overlaid on existing cellular infrastructure,
is seen as a key feature in next-generation cellular systems. In this paper,
the problem of user association in the downlink of small cell networks (SCNs)
is considered. The problem is formulated as a many-to-one matching game in
which the users and SCBSs rank one another based on utility functions that
account for both the achievable performance, in terms of rate and fairness to
cell edge users, as captured by newly proposed priorities. To solve this game,
a novel distributed algorithm that can reach a stable matching is proposed.
Simulation results show that the proposed approach yields an average utility
gain of up to 65% compared to a common association algorithm that is based on
received signal strength. Compared to the classical deferred acceptance
algorithm, the results also show a 40% utility gain and a more fair utility
distribution among the users.Comment: 5 page
Spatial networks with wireless applications
Many networks have nodes located in physical space, with links more common
between closely spaced pairs of nodes. For example, the nodes could be wireless
devices and links communication channels in a wireless mesh network. We
describe recent work involving such networks, considering effects due to the
geometry (convex,non-convex, and fractal), node distribution,
distance-dependent link probability, mobility, directivity and interference.Comment: Review article- an amended version with a new title from the origina
Average Rate of Downlink Heterogeneous Cellular Networks over Generalized Fading Channels - A Stochastic Geometry Approach
In this paper, we introduce an analytical framework to compute the average
rate of downlink heterogeneous cellular networks. The framework leverages
recent application of stochastic geometry to other-cell interference modeling
and analysis. The heterogeneous cellular network is modeled as the
superposition of many tiers of Base Stations (BSs) having different transmit
power, density, path-loss exponent, fading parameters and distribution, and
unequal biasing for flexible tier association. A long-term averaged maximum
biased-received-power tier association is considered. The positions of the BSs
in each tier are modeled as points of an independent Poisson Point Process
(PPP). Under these assumptions, we introduce a new analytical methodology to
evaluate the average rate, which avoids the computation of the Coverage
Probability (Pcov) and needs only the Moment Generating Function (MGF) of the
aggregate interference at the probe mobile terminal. The distinguishable
characteristic of our analytical methodology consists in providing a tractable
and numerically efficient framework that is applicable to general fading
distributions, including composite fading channels with small- and mid-scale
fluctuations. In addition, our method can efficiently handle correlated
Log-Normal shadowing with little increase of the computational complexity. The
proposed MGF-based approach needs the computation of either a single or a
two-fold numerical integral, thus reducing the complexity of Pcov-based
frameworks, which require, for general fading distributions, the computation of
a four-fold integral.Comment: Accepted for publication in IEEE Transactions on Communications, to
appea
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