9,276 research outputs found
Modeling Heterogeneous Network Interference Using Poisson Point Processes
Cellular systems are becoming more heterogeneous with the introduction of low
power nodes including femtocells, relays, and distributed antennas.
Unfortunately, the resulting interference environment is also becoming more
complicated, making evaluation of different communication strategies
challenging in both analysis and simulation. Leveraging recent applications of
stochastic geometry to analyze cellular systems, this paper proposes to analyze
downlink performance in a fixed-size cell, which is inscribed within a weighted
Voronoi cell in a Poisson field of interferers. A nearest out-of-cell
interferer, out-of-cell interferers outside a guard region, and cross-tier
interference are included in the interference calculations. Bounding the
interference power as a function of distance from the cell center, the total
interference is characterized through its Laplace transform. An equivalent
marked process is proposed for the out-of-cell interference under additional
assumptions. To facilitate simplified calculations, the interference
distribution is approximated using the Gamma distribution with second order
moment matching. The Gamma approximation simplifies calculation of the success
probability and average rate, incorporates small-scale and large-scale fading,
and works with co-tier and cross-tier interference. Simulations show that the
proposed model provides a flexible way to characterize outage probability and
rate as a function of the distance to the cell edge.Comment: Submitted to the IEEE Transactions on Signal Processing, July 2012,
Revised December 201
On Modeling Heterogeneous Wireless Networks Using Non-Poisson Point Processes
Future wireless networks are required to support 1000 times higher data rate,
than the current LTE standard. In order to meet the ever increasing demand, it
is inevitable that, future wireless networks will have to develop seamless
interconnection between multiple technologies. A manifestation of this idea is
the collaboration among different types of network tiers such as macro and
small cells, leading to the so-called heterogeneous networks (HetNets).
Researchers have used stochastic geometry to analyze such networks and
understand their real potential. Unsurprisingly, it has been revealed that
interference has a detrimental effect on performance, especially if not modeled
properly. Interference can be correlated in space and/or time, which has been
overlooked in the past. For instance, it is normally assumed that the nodes are
located completely independent of each other and follow a homogeneous Poisson
point process (PPP), which is not necessarily true in real networks since the
node locations are spatially dependent. In addition, the interference
correlation created by correlated stochastic processes has mostly been ignored.
To this end, we take a different approach in modeling the interference where we
use non-PPP, as well as we study the impact of spatial and temporal correlation
on the performance of HetNets. To illustrate the impact of correlation on
performance, we consider three case studies from real-life scenarios.
Specifically, we use massive multiple-input multiple-output (MIMO) to
understand the impact of spatial correlation; we use the random medium access
protocol to examine the temporal correlation; and we use cooperative relay
networks to illustrate the spatial-temporal correlation. We present several
numerical examples through which we demonstrate the impact of various
correlation types on the performance of HetNets.Comment: Submitted to IEEE Communications Magazin
Wireless networks appear Poissonian due to strong shadowing
Geographic locations of cellular base stations sometimes can be well fitted
with spatial homogeneous Poisson point processes. In this paper we make a
complementary observation: In the presence of the log-normal shadowing of
sufficiently high variance, the statistics of the propagation loss of a single
user with respect to different network stations are invariant with respect to
their geographic positioning, whether regular or not, for a wide class of
empirically homogeneous networks. Even in perfectly hexagonal case they appear
as though they were realized in a Poisson network model, i.e., form an
inhomogeneous Poisson point process on the positive half-line with a power-law
density characterized by the path-loss exponent. At the same time, the
conditional distances to the corresponding base stations, given their observed
propagation losses, become independent and log-normally distributed, which can
be seen as a decoupling between the real and model geometry. The result applies
also to Suzuki (Rayleigh-log-normal) propagation model. We use
Kolmogorov-Smirnov test to empirically study the quality of the Poisson
approximation and use it to build a linear-regression method for the
statistical estimation of the value of the path-loss exponent
A New Cell Association Scheme In Heterogeneous Networks
Cell association scheme determines which base station (BS) and mobile user
(MU) should be associated with and also plays a significant role in determining
the average data rate a MU can achieve in heterogeneous networks. However, the
explosion of digital devices and the scarcity of spectra collectively force us
to carefully re-design cell association scheme which was kind of taken for
granted before. To address this, we develop a new cell association scheme in
heterogeneous networks based on joint consideration of the
signal-to-interference-plus-noise ratio (SINR) which a MU experiences and the
traffic load of candidate BSs1. MUs and BSs in each tier are modeled as several
independent Poisson point processes (PPPs) and all channels experience
independently and identically distributed ( i.i.d.) Rayleigh fading. Data rate
ratio and traffic load ratio distributions are derived to obtain the tier
association probability and the average ergodic MU data rate. Through numerical
results, We find that our proposed cell association scheme outperforms cell
range expansion (CRE) association scheme. Moreover, results indicate that
allocating small sized and high-density BSs will improve spectral efficiency if
using our proposed cell association scheme in heterogeneous networks.Comment: Accepted by IEEE ICC 2015 - Next Generation Networking Symposiu
Downlink Coverage Analysis in a Heterogeneous Cellular Network
In this paper, we consider the downlink signal-to-interference-plus-noise
ratio (SINR) analysis in a heterogeneous cellular network with K tiers. Each
tier is characterized by a base-station (BS) arrangement according to a
homogeneous Poisson point process with certain BS density, transmission power,
random shadow fading factors with arbitrary distribution, arbitrary path-loss
exponent and a certain bias towards admitting the mobile-station (MS). The MS
associates with the BS that has the maximum SINR under the open access cell
association scheme. For such a general setting, we provide an analytical
characterization of the coverage probability at the MS.Comment: 6 pages, 5 figures, submitted to IEEE Globecom 2012 - Wireless
Communications Symposium on Apr 2, 201
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