| Autor: |
Thampi, Ajay, Kaleshi, Dritan, Randall, Peter, Featherstone, Walter, Armour, Simon |
| Zdroj: |
2012 International Symposium on Wireless Communication Systems (ISWCS); 1/ 1/2012, p909-913, 5p |
| Abstrakt: |
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 multiple coverage problems. [ABSTRACT FROM PUBLISHER] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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