1,006 research outputs found
SINR-based k-coverage probability in cellular networks with arbitrary shadowing
We give numerically tractable, explicit integral expressions for the
distribution of the signal-to-interference-and-noise-ratio (SINR) experienced
by a typical user in the down-link channel from the k-th strongest base
stations of a cellular network modelled by Poisson point process on the plane.
Our signal propagation-loss model comprises of a power-law path-loss function
with arbitrarily distributed shadowing, independent across all base stations,
with and without Rayleigh fading. Our results are valid in the whole domain of
SINR, in particular for SINR<1, where one observes multiple coverage. In this
latter aspect our paper complements previous studies reported in [Dhillon et
al. JSAC 2012]
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 Comprehensive Analysis of 5G Heterogeneous Cellular Systems operating over - Shadowed Fading Channels
Emerging cellular technologies such as those proposed for use in 5G
communications will accommodate a wide range of usage scenarios with diverse
link requirements. This will include the necessity to operate over a versatile
set of wireless channels ranging from indoor to outdoor, from line-of-sight
(LOS) to non-LOS, and from circularly symmetric scattering to environments
which promote the clustering of scattered multipath waves. Unfortunately, many
of the conventional fading models adopted in the literature to develop network
models lack the flexibility to account for such disparate signal propagation
mechanisms. To bridge the gap between theory and practical channels, we
consider - shadowed fading, which contains as special cases, the
majority of the linear fading models proposed in the open literature, including
Rayleigh, Rician, Nakagami-m, Nakagami-q, One-sided Gaussian, -,
-, and Rician shadowed to name but a few. In particular, we apply an
orthogonal expansion to represent the - shadowed fading
distribution as a simplified series expression. Then using the series
expressions with stochastic geometry, we propose an analytic framework to
evaluate the average of an arbitrary function of the SINR over -
shadowed fading channels. Using the proposed method, we evaluate the spectral
efficiency, moments of the SINR, bit error probability and outage probability
of a -tier HetNet with classes of BSs, differing in terms of the
transmit power, BS density, shadowing characteristics and small-scale fading.
Building upon these results, we provide important new insights into the network
performance of these emerging wireless applications while considering a diverse
range of fading conditions and link qualities
A Tractable Approach to Coverage and Rate in Cellular Networks
Cellular networks are usually modeled by placing the base stations on a grid,
with mobile users either randomly scattered or placed deterministically. These
models have been used extensively but suffer from being both highly idealized
and not very tractable, so complex system-level simulations are used to
evaluate coverage/outage probability and rate. More tractable models have long
been desirable. We develop new general models for the multi-cell
signal-to-interference-plus-noise ratio (SINR) using stochastic geometry. Under
very general assumptions, the resulting expressions for the downlink SINR CCDF
(equivalent to the coverage probability) involve quickly computable integrals,
and in some practical special cases can be simplified to common integrals
(e.g., the Q-function) or even to simple closed-form expressions. We also
derive the mean rate, and then the coverage gain (and mean rate loss) from
static frequency reuse. We compare our coverage predictions to the grid model
and an actual base station deployment, and observe that the proposed model is
pessimistic (a lower bound on coverage) whereas the grid model is optimistic,
and that both are about equally accurate. In addition to being more tractable,
the proposed model may better capture the increasingly opportunistic and dense
placement of base stations in future networks.Comment: Submitted to IEEE Transactions on Communication
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