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Performance Analysis of Infrastructure Sharing Techniques in Cellular Networks: A Percolation Theory Approach

Hao Lin, Mustafa A. Kishk, Mohamed-Slim Alouini

TL;DR

The paper addresses the problem of achieving large-scale continuous 5G service coverage under different infrastructure sharing strategies. It develops a percolation-theory framework for SINR-based coverage, introducing an average coverage radius to approximate low-density networks via Gilbert disk models. It derives critical BS-density conditions for no sharing, active sharing, and passive sharing, and validates the approach with Monte Carlo simulations showing that active sharing yields the strongest connectivity. The findings provide a tractable method for operators to evaluate sharing strategies and deployment plans, with implications for cost reduction and digital inclusion. The work bridges percolation theory with practical network sharing decisions, offering quantitative guidance for ensuring continuous service areas at scale.

Abstract

In the context of 5G, infrastructure sharing has been identified as a potential solution to reduce the investment costs of cellular networks. In particular, it can help low-income regions build 5G networks more affordably and further bridge the digital divide. There are two main kinds of infrastructure sharing: passive sharing (i.e. site sharing) and active sharing (i.e. access sharing), which require mobile network operators (MNOs) to share their non-electronic elements or electronic elements, respectively. Because co-construction and sharing can achieve broader coverage with lower investment, through percolation theory, we investigate how different sharing strategies can deliver large-scale continuous services. First, we examine the percolation characteristics in signal-to-interference-plus-noise ratio (SINR) coverage graphs and the necessary conditions for percolation. Second, we propose an 'average coverage radius' to approximate the SINR graph with a low base station (BS) density based on the Gilbert disk model. Finally, we estimate the critical conditions of BS densities of MNOs for different sharing strategies and compare the percolation probabilities under different infrastructure sharing strategies.

Performance Analysis of Infrastructure Sharing Techniques in Cellular Networks: A Percolation Theory Approach

TL;DR

The paper addresses the problem of achieving large-scale continuous 5G service coverage under different infrastructure sharing strategies. It develops a percolation-theory framework for SINR-based coverage, introducing an average coverage radius to approximate low-density networks via Gilbert disk models. It derives critical BS-density conditions for no sharing, active sharing, and passive sharing, and validates the approach with Monte Carlo simulations showing that active sharing yields the strongest connectivity. The findings provide a tractable method for operators to evaluate sharing strategies and deployment plans, with implications for cost reduction and digital inclusion. The work bridges percolation theory with practical network sharing decisions, offering quantitative guidance for ensuring continuous service areas at scale.

Abstract

In the context of 5G, infrastructure sharing has been identified as a potential solution to reduce the investment costs of cellular networks. In particular, it can help low-income regions build 5G networks more affordably and further bridge the digital divide. There are two main kinds of infrastructure sharing: passive sharing (i.e. site sharing) and active sharing (i.e. access sharing), which require mobile network operators (MNOs) to share their non-electronic elements or electronic elements, respectively. Because co-construction and sharing can achieve broader coverage with lower investment, through percolation theory, we investigate how different sharing strategies can deliver large-scale continuous services. First, we examine the percolation characteristics in signal-to-interference-plus-noise ratio (SINR) coverage graphs and the necessary conditions for percolation. Second, we propose an 'average coverage radius' to approximate the SINR graph with a low base station (BS) density based on the Gilbert disk model. Finally, we estimate the critical conditions of BS densities of MNOs for different sharing strategies and compare the percolation probabilities under different infrastructure sharing strategies.

Paper Structure

This paper contains 24 sections, 11 theorems, 75 equations, 9 figures, 1 table.

Table of Contents

  1. Introduction
  2. Related Work
  3. Contributions
  4. System Model
  5. Percolation in SINR coverage graph
  6. Serving areas of BSs
  7. Sub-critical regions
  8. Average coverage radius for low-density network
  9. Continuous Percolation in Gilbert disk model
  10. Percolation on Different Sharing Strategy
  11. No Sharing
  12. Active Sharing
  13. Passive Sharing
  14. Simulation results and discussion
  15. Conclusion
  16. ...and 9 more sections

Key Result

Theorem 1

For a large-scale cellular network, the union of the strongest coverage areas (SCAs) of BSs is the same as the union of coverage areas (CAs) of BSs, that is: Therefore, the face percolation of CAs $\{\Psi_i\}$ is equivalent to the percolation of SCAs $\{\Psi_i\cap\Omega_i\}$.

Figures (9)

  • Figure 1: Comparison of 'no sharing', 'active sharing (access sharing)' and 'passive sharing (site sharing)'. Active sharing allows UEs of each MNO to switch the spectrum and access another MNO's BSs. Passive sharing allows each MNO to deploy its transceivers on another MNO's BSs.
  • Figure 2: Mathematical models and geometric interpretations considered when studying different sharing strategies based on the Gilbert disk model.
  • Figure 3: The relationship between the proportion of areas effectively covered by BSs providing the same MNO's service.
  • Figure 4: Percolation probability in different sharing strategies.
  • Figure 5: SINR coverage proportion in different sharing strategies.
  • ...and 4 more figures

Theorems & Definitions (13)

  • Theorem 1
  • Theorem 2
  • Remark 1
  • Theorem 3
  • Remark 2
  • Theorem 4
  • Theorem 5
  • Theorem 6
  • Corollary 1
  • Theorem 7
  • ...and 3 more