699 research outputs found
Simple Approximations of the SIR Meta Distribution in General Cellular Networks
Compared to the standard success (coverage) probability, the meta
distribution of the signal-to-interference ratio (SIR) provides much more
fine-grained information about the network performance. We consider general
heterogeneous cellular networks (HCNs) with base station tiers modeled by
arbitrary stationary and ergodic non-Poisson point processes. The exact
analysis of non-Poisson network models is notoriously difficult, even in terms
of the standard success probability, let alone the meta distribution. Hence we
propose a simple approach to approximate the SIR meta distribution for
non-Poisson networks based on the ASAPPP ("approximate SIR analysis based on
the Poisson point process") method. We prove that the asymptotic horizontal gap
between its standard success probability and that for the Poisson point
process exactly characterizes the gap between the th moment of the
conditional success probability, as the SIR threshold goes to . The gap
allows two simple approximations of the meta distribution for general
HCNs: 1) the per-tier approximation by applying the shift to each tier
and 2) the effective gain approximation by directly shifting the meta
distribution for the homogeneous independent Poisson network. Given the
generality of the model considered and the fine-grained nature of the meta
distribution, these approximations work surprisingly well.Comment: This paper has been accepted in the IEEE Transactions on
Communications. 14 pages, 13 figure
A Dominant Interferer-based Approximation for Uplink SINR Meta Distribution in Cellular Networks
This work studies the signal-to-interference-plus-noise-ratio (SINR) meta
distribution for the uplink transmission of a Poisson network with Rayleigh
fading by using the dominant interferer-based approximation. The proposed
approach relies on computing the mix of exact and mean-field analysis of
interference. In particular, it requires the distance distribution of the
nearest interferer and the conditional average of the rest of the interference.
Using the widely studied fractional path-loss inversion power control and
modeling the spatial locations of base stations (BSs) by a Poisson point
process (PPP), we obtain the meta distribution based on the proposed method and
compare it with the traditional beta approximation, as well as the exact
results obtained via Monte-Carlo simulations. Our numerical results validate
that the proposed method shows good matching and is time competitive.Comment: arXiv admin note: text overlap with arXiv:2302.0357
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