1,878 research outputs found
How user throughput depends on the traffic demand in large cellular networks
Little's law allows to express the mean user throughput in any region of the
network as the ratio of the mean traffic demand to the steady-state mean number
of users in this region. Corresponding statistics are usually collected in
operational networks for each cell. Using ergodic arguments and Palm theoretic
formalism, we show that the global mean user throughput in the network is equal
to the ratio of these two means in the steady state of the "typical cell".
Here, both means account for double averaging: over time and network geometry,
and can be related to the per-surface traffic demand, base-station density and
the spatial distribution of the SINR. This latter accounts for network
irregularities, shadowing and idling cells via cell-load equations. We validate
our approach comparing analytical and simulation results for Poisson network
model to real-network cell-measurements
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
Spatial spectrum and energy efficiency of random cellular networks
It is a great challenge to evaluate the network performance of cellular
mobile communication systems. In this paper, we propose new spatial spectrum
and energy efficiency models for Poisson-Voronoi tessellation (PVT) random
cellular networks. To evaluate the user access the network, a Markov chain
based wireless channel access model is first proposed for PVT random cellular
networks. On that basis, the outage probability and blocking probability of PVT
random cellular networks are derived, which can be computed numerically.
Furthermore, taking into account the call arrival rate, the path loss exponent
and the base station (BS) density in random cellular networks, spatial spectrum
and energy efficiency models are proposed and analyzed for PVT random cellular
networks. Numerical simulations are conducted to evaluate the network spectrum
and energy efficiency in PVT random cellular networks.Comment: appears in IEEE Transactions on Communications, April, 201
- …