Coverage Gains from the Static Cooperation of Mutually Nearest Neighbours

TL;DR

This paper investigates how static cooperation between mutually nearest neighbor pairs in cellular networks, modeled by Poisson Point Processes, can significantly improve coverage probability, with gains up to 15%.

Contribution

It introduces a clustering model based on mutually nearest neighbors and derives exact coverage probability expressions for cooperative pairs in Poisson networks.

Findings

Coverage gains up to 15% with cooperation schemes.

Exact coverage probability formulas for the proposed model.

Applicable to various cooperation strategies.

Abstract

Cooperation in cellular networks has been recently suggested as a promising scheme to improve system performance. In this work, clusters are formed based on the Mutually Nearest Neighbour relation, which defines which stations cooperate in pair and which do not. When node positions follow a Poisson Point Process (PPP) the performance of the original clustering model can be approximated by another one, formed by the superposition of two PPPs (one for the singles and one for the pairs) equipped with adequate marks. This allows to derive exact expressions for the network coverage probability under two user-cluster association rules. Numerical evaluation shows coverage gains from different signal cooperation schemes that can reach up to 15% compared to the standard non-cooperative network coverage. The analysis is general and can be applied to any type of cooperation or coordination between pairs of transmitting nodes.