933 research outputs found
Analysis of Static Cellular Cooperation between Mutually Nearest Neighboring Nodes
Cooperation in cellular networks is a promising scheme to improve system
performance. Existing works consider that a user dynamically chooses the
stations that cooperate for his/her service, but such assumption often has
practical limitations. Instead, cooperation groups can be predefined and
static, with nodes linked by fixed infrastructure. To analyze such a potential
network, we propose a grouping method based on node proximity. With the
Mutually Nearest Neighbour Relation, we allow the formation of singles and
pairs of nodes. Given an initial topology for the stations, two new point
processes are defined, one for the singles and one for the pairs. We derive
structural characteristics for these processes and analyse the resulting
interference fields. When the node positions follow a Poisson Point Process
(PPP) the processes of singles and pairs are not Poisson. However, the
performance of the original model can be approximated by the superposition of
two PPPs. This allows the derivation of exact expressions for the coverage
probability. Numerical evaluation shows coverage gains from different signal
cooperation that can reach up to 15% compared to the standard noncooperative
coverage. The analysis is general and can be applied to any type of cooperation
in pairs of transmitting nodes.Comment: 17 pages, double column, Appendices A-D, 9 Figures, 18 total
subfigures. arXiv admin note: text overlap with arXiv:1604.0464
Wireless Node Cooperation with Resource Availability Constraints
Base station cooperation is a promising scheme to improve network performance
for next generation cellular networks. Up to this point research has focused on
station grouping criteria based solely on geographic proximity. However, for
the cooperation to be meaningful, each station participating in a group should
have sufficient available resources to share with others. In this work we
consider an alternative grouping criterion based on a distance that considers
both geographic proximity and available resources of the stations. When the
network is modelled by a Poisson Point Process, we derive analytical formulas
on the proportion of cooperative pairs or single stations, and the expected sum
interference from each of the groups. The results illustrate that cooperation
gains strongly depend on the distribution of available resources over the
network.Comment: submitted, 12 pages, double-column, 7 figures, 8 sub-figures in tota
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
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