Analysis of Static Cellular Cooperation between Mutually Nearest Neighboring Nodes

TL;DR

This paper analyzes static cooperation in cellular networks using a mutual nearest neighbor grouping method, deriving models and coverage probability expressions, showing up to 15% performance gains over noncooperative systems.

Contribution

It introduces a novel static grouping method based on mutual nearest neighbors and derives analytical models for coverage probability in such cooperative networks.

Findings

Coverage gains up to 15% with cooperation.

Derived exact coverage probability expressions.

Superposition of two PPPs approximates the network performance.

Abstract

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.