120 research outputs found
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
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
Stochastic Geometric Analysis of Energy-Efficient Dense Cellular Networks
Dense cellular networks (DenseNets) are fast becoming a reality with the large scale deployment of base stations aimed at meeting the explosive data traffic demand. In legacy systems, however, this comes at the cost of higher network interference and energy consumption. In order to support network densification in a sustainable manner, the system behavior should be made “load-proportional” thus allowing certain portions of the network to activate on-demand. In this paper, we develop an analytical framework using tools from stochastic geometry theory for the performance analysis of DenseNets where load-awareness is explicitly embedded in the design. The proposed model leverages on a flexible cellular network architecture where there is a complete separation of the data and signaling communications functionalities. Using this stochastic geometric framework, we identify the most energy-efficient deployment solution for meeting certain minimum service criteria and analyze the corresponding power savings through dynamic sleep modes. According to state-of-the-art system parameters, a homogeneous pico deployment for the data plane with a separate layer of signaling macro-cells is revealed to be the most energy-efficient solution in future dense urban environments
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