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Python Simulator for a Stochastic Geometry Based Network

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Spectrum Sharing in Cellular Networks (A Stochastic Geometry Based Approach for Cellular Network)

This project was based around the spectrum sharing concept between mobile network operators. A stochastic geometry cellular network based on the Poisson Point Process is developed and Monte Carlo method is utilized to determine network performance metrics. It allows an easy evaluation of different protocols for cellular networks. There are some useful bits of code if you look hard enough.

Opportunities:

  • Determine the optimal base station association in a stochastic geometry based network for users
  • Determine the path loss for users
  • Evaluate the Signal-to-Noise (SNR) ratio of users in a network
  • Evaluate the Signal-to-Interference-Noise (SINR) ratio of users in a network
  • Evaluate the throughput of users in a network
  • Determine spectrum sharing between multiple operators

Configurable simulation parameters:

  1. Transmit power of basestation
  2. User density
  3. Basestation density
  4. Carrier frequency
  5. Area of simulation
  6. Total bandwidth available
  7. Number of iterations for Monte Carlo simulation

Installation

Clone the project in your desired directory. Run the main file in a Python3 interpreter.

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Python Simulator for a Stochastic Geometry Based Network

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