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A Game-Theoretic Framework for Coexistence of WiFi and Cellular Networks in the 6-GHz Unlicensed Spectrum

Aniq Ur Rahman, Mustafa A. Kishk, Mohamed-Slim Alouini

TL;DR

The proposed framework allows only a fraction of the cellular base stations and WiFi access points to use the 6-GHz band so that sources of interference are spatially segregated and made sparse, thereby decreasing the overall interference to each other.

Abstract

We study the interaction of WiFi and 5G cellular networks as they exploit the recently unlocked 6-GHz spectrum for unlicensed access while conforming to the constraints imposed by the incumbent users. We derive the theoretical performance metrics for users of each radio access technology using stochastic geometry, thereby capturing the aggregate behaviour of the network. We propose a framework where the portions of cellular and WiFi networks are grouped to form entities that interact to satisfy their QoS demands by playing a non-cooperative game. The action of an entity corresponds to the fraction of its network elements operating in the 6-GHz band. Due to the decentralized nature of the game, we find the solution using distributed Best Response Algorithm, which improves the average datarate by 11.37% and 18.59% for cellular and WiFi networks, respectively. The results demonstrate how the system parameters affect the performance of a network at equilibrium and highlight the throughput gains as a result of using the 6-GHz bands. We tested our framework on a real-world setup with actual network locations, showing that practical implementation of multi-entity spectrum sharing is feasible even when the spatial distribution of the network and users are non-homogeneous.

A Game-Theoretic Framework for Coexistence of WiFi and Cellular Networks in the 6-GHz Unlicensed Spectrum

TL;DR

The proposed framework allows only a fraction of the cellular base stations and WiFi access points to use the 6-GHz band so that sources of interference are spatially segregated and made sparse, thereby decreasing the overall interference to each other.

Abstract

We study the interaction of WiFi and 5G cellular networks as they exploit the recently unlocked 6-GHz spectrum for unlicensed access while conforming to the constraints imposed by the incumbent users. We derive the theoretical performance metrics for users of each radio access technology using stochastic geometry, thereby capturing the aggregate behaviour of the network. We propose a framework where the portions of cellular and WiFi networks are grouped to form entities that interact to satisfy their QoS demands by playing a non-cooperative game. The action of an entity corresponds to the fraction of its network elements operating in the 6-GHz band. Due to the decentralized nature of the game, we find the solution using distributed Best Response Algorithm, which improves the average datarate by 11.37% and 18.59% for cellular and WiFi networks, respectively. The results demonstrate how the system parameters affect the performance of a network at equilibrium and highlight the throughput gains as a result of using the 6-GHz bands. We tested our framework on a real-world setup with actual network locations, showing that practical implementation of multi-entity spectrum sharing is feasible even when the spatial distribution of the network and users are non-homogeneous.

Paper Structure

This paper contains 30 sections, 6 theorems, 13 equations, 16 figures, 1 table, 1 algorithm.

Table of Contents

  1. Introduction
  2. Related Works
  3. Coexistence in the Unlicensed Spectra
  4. Stochastic Geometry for Studying Coexistence
  5. Spectrum Sharing using Game Theory
  6. Contributions
  7. System Model
  8. Network Deployment
  9. Incumbent Users
  10. WiFi Network
  11. Cellular Network
  12. Downlink Interference
  13. Multi-Entity Competition
  14. Performance Metrics
  15. Coverage Probability
  16. ...and 15 more sections

Key Result

Lemma 1

The coverage probability for a cellular user operating in the licensed band is: where $\zeta(\gamma, \alpha) = \frac{\gamma^{\frac{2}{\alpha}}}{2} \int_{\gamma^{-\frac{2}{\alpha}}}^{\infty} \frac{1}{1 + x^{\frac{\alpha}{2}}} \, dx.$

Figures (16)

  • Figure 1: System Illustration.
  • Figure 2: Sample network deployment showing $\Phi_z, \Xi_{\rho}, \hat{\Phi}_c, \hat{\Phi}_w$. The exclusion zones of radius $\rho$ are drawn around the incumbent users as yellow circles. Parameters: $\lambda_z= 1~{\rm user}/{\rm km}^2$, $\lambda_c= 25~{\rm BS}/{\rm km}^2$, $\lambda_w=100~{\rm AP}/{\rm km}^2$, $\rho = 200~{\rm m}$.
  • Figure 3: Division of the network among a set of Entities.
  • Figure 4: Coverage probability for the cellular and WiFi users operating in the licensed and unlicensed spectra. $\lambda_z= 1~{\rm user}/{\rm km}^2$, $\lambda_c= 25~{\rm BS}/{\rm km}^2$, $\lambda_w=100~{\rm AP}/{\rm km}^2$, $\rho = 200~{\rm m}$, $\rho_w = 50~{\rm m}$, $p_z = 1~{\rm W}$, $p_c = 2~{\rm W}$, $p_w = 1~{\rm W}$, $\delta_c = 0.7$, $\delta_w = 0.2$.
  • Figure 5: Average cellular and WiFi datarates. Parameters: $|\mathcal{E}|=1$, $\lambda_z= 1~{\rm user}/{\rm km}^2$, $\lambda_c= 25~{\rm BS}/{\rm km}^2$, $\lambda_w=100~{\rm AP}/{\rm km}^2$, $\rho = 200~{\rm m}$, $\rho_w = 50~{\rm m}$, $p_z = 1~{\rm W}$, $p_c = 2~{\rm W}$, $p_w = 1~{\rm W}$, $B_U= 240~{\rm MHz}$, $B_{c|L}= 80~{\rm MHz}$, $B_{w|L}= 80~{\rm MHz}$, $\gamma = 10~{\rm dB}$.
  • ...and 11 more figures

Theorems & Definitions (21)

  • Definition 1
  • Definition 2
  • Definition 3
  • Definition 4
  • Lemma 1
  • proof
  • Lemma 2
  • proof
  • Lemma 3
  • proof
  • ...and 11 more