An Analytical Framework for Multi-Cell Cooperation via Stochastic Geometry and Large Deviations
Kaibin Huang, Jeffrey G. Andrews

TL;DR
This paper develops an analytical framework using stochastic geometry and large deviations to evaluate multi-cell cooperation performance in dense cellular networks, revealing how outage probability scales with cooperation size and scattering environment.
Contribution
It introduces a novel Poisson tessellation model for cellular networks and applies advanced mathematical techniques to analyze outage probability, providing insights beyond simplified models.
Findings
Outage probability decreases sub-exponentially with increasing cooperation for sparse scattering.
In rich scattering, outage probability follows a power law with an exponent proportional to signal diversity.
Cluster-edge mobiles are identified as the main bottleneck for network coverage.
Abstract
Multi-cell cooperation (MCC) is an approach for mitigating inter-cell interference in dense cellular networks. Existing studies on MCC performance typically rely on either over-simplified Wyner-type models or complex system-level simulations. The promising theoretical results (typically using Wyner models) seem to materialize neither in complex simulations nor in practice. To more accurately investigate the theoretical performance of MCC, this paper models an entire plane of interfering cells as a Poisson random tessellation. The base stations (BSs) are then clustered using a regular lattice, whereby BSs in the same cluster mitigate mutual interference by beamforming with perfect channel state information. Techniques from stochastic geometry and large deviation theory are applied to analyze the outage probability as a function of the mobile locations, scattering environment, and the…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Cooperative Communication and Network Coding · Wireless Communication Security Techniques
