A sparse sampling algorithm for self-optimisation of coverage in LTE networks

@article{Thampi2012ASS,
  title={A sparse sampling algorithm for self-optimisation of coverage in LTE networks},
  author={Ajay Thampi and Dritan Kaleshi and Peter Randall and Walter Featherstone and Simon Armour},
  journal={2012 International Symposium on Wireless Communication Systems (ISWCS)},
  year={2012},
  pages={909-913}
}
Coverage optimisation is an important self-organising capability that operators would like to have in LTE networks. This paper applies a Reinforcement Learning (RL) based Sparse Sampling algorithm for the self-optimisation of coverage through antenna tilting. This algorithm is better than supervised learning and Q-learning based algorithms as it has the ability to adapt to network environments without prior knowledge, handle large state spaces, perform self-healing and potentially focus on… CONTINUE READING

References

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LTE SON: Network Management Automation for Operational Efficiency

  • S Hamalainen
  • 2012
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