Coverage Gains from the Static Cooperation of Mutually Nearest Neighbours

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.

[1]  Jeffrey G. Andrews,et al.  A Tractable Approach to Coverage and Rate in Cellular Networks , 2010, IEEE Transactions on Communications.

[2]  Robert W. Heath,et al.  Interference Coordination: Random Clustering and Adaptive Limited Feedback , 2012, IEEE Transactions on Signal Processing.

[3]  François Baccelli,et al.  Stochastic Geometry and Wireless Networks, Volume 1: Theory , 2009, Found. Trends Netw..

[4]  Francois Baccelli,et al.  A Stochastic Geometry Framework for Analyzing Pairwise-Cooperative Cellular Networks , 2013, IEEE Transactions on Wireless Communications.

[5]  Martin Haenggi,et al.  Success probabilities in Gauss-Poisson networks with and without cooperation , 2014, 2014 IEEE International Symposium on Information Theory.

[6]  Laurent Decreusefond,et al.  Analyzing interference from static cellular cooperation using the Nearest Neighbour Model , 2015, 2015 13th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt).

[7]  S. Ross A First Course in Probability , 1977 .

[8]  Holger Paul Keeler,et al.  Studying the SINR Process of the Typical User in Poisson Networks Using Its Factorial Moment Measures , 2014, IEEE Transactions on Information Theory.

[9]  Wei Yu,et al.  Multi-Cell MIMO Cooperative Networks: A New Look at Interference , 2010, IEEE Journal on Selected Areas in Communications.

[10]  Jeffrey G. Andrews,et al.  A Tractable Model for Noncoherent Joint-Transmission Base Station Cooperation , 2013, IEEE Transactions on Wireless Communications.

[11]  Angelika Bayer,et al.  A First Course In Probability , 2016 .

[12]  Olle Häggström,et al.  Nearest Neighbor and Hard Sphere Models in Continuum Percolation , 1996 .

[13]  Peter Han Joo Chong,et al.  Fundamentals of Cluster-Centric Content Placement in Cache-Enabled Device-to-Device Networks , 2015, IEEE Transactions on Communications.

[14]  Martin Haenggi,et al.  Coordinated Multipoint Joint Transmission in Heterogeneous Networks , 2014, IEEE Transactions on Communications.

[15]  Stefan Brueck,et al.  A 0–1 program to form minimum cost clusters in the downlink of cooperating base stations , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).