Sökning: "Remote Electrical Tilt"

Visar resultat 1 - 5 av 14 uppsatser innehållade orden Remote Electrical Tilt.

1. 1. Data Driven Model Identification for Remote Electrical Tilt Systems

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Raphaël Ashruf; [2023]
   Nyckelord :;

   Sammanfattning : This thesis explores the use of supervised machine learning for modelling the dynamics of Remote Electrical Tilt (RET) telecom systems. Three methodologies, including linear regressionfor linear dynamics models, Gaussian Process (GP) regression, and Recurrent Neural Networks (RNN) with Gated Recurrent Units (GRU) are proposed. LÄS MER

3. 2. Model-based Residual Policy Learning for Sample Efficient Mobile Network Optimization

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Viktor Eriksson Möllerstedt; [2022]
   Nyckelord :Reinforcement Learning; Sample Efficiency; Model-based; Expert Policy; Remote Electrical Tilt; Telecommunication; Förstärkande inlärning; dataeffektivitet; modell-baserad; expert-policy; fjärrstyrning av antenners nedåtlutning; telekommunikation;

   Sammanfattning : Reinforcement learning is a powerful tool which enables an agent to learn how to control complex systems. However, during the early phases of training, the performance is often poor. LÄS MER

4. 3. Personalization with Reward Shaping for Remote Electrical Tilt Optimization

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Daniel Schmekel; [2022]
   Nyckelord :Reward shaping; personalization; RET optimization; Reinforcement learning; Reward shaping; individuell anpassning; RET optimering;

   Sammanfattning : Remote electrical tilt (RET) optimization involves maximizing the coverage and minimizing interference for antennas in a cellular network. A RET optimization problem typically has many of antennas, each of which has little data. Reinforcement learning (RL) agents have recently been deployed to solve RET optimization problems [1, 2]. LÄS MER

5. 4. Explainable Reinforcement Learning for Remote Electrical Tilt Optimization

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Artin Mirzaian; [2022]
   Nyckelord :Reinforcement Learning; Explainability; Explainable Reinforcement Learning; Machine Learning; Artificial Intelligence; Remote Electrical tilt optimization.; Förstärkningsinlärning; Förklarbarhet; Förklarbar Förstärkningsinlärning; Maskininlärning; Artificiell Intelligens; Optimering av Fjärrlutning.;

   Sammanfattning : Controlling antennas’ vertical tilt through Remote Electrical Tilt (RET) is an effective method to optimize network performance. Reinforcement Learning (RL) algorithms such as Deep Reinforcement Learning (DRL) have been shown to be successful for RET optimization. LÄS MER

7. 5. Bridging Sim-to-Real Gap in Offline Reinforcement Learning for Antenna Tilt Control in Cellular Networks

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Mayank Gulati; [2021]
   Nyckelord :reinforcement learning; transfer learning; simulation-to-reality; simulator; realworld; real-world network data; remote electrical tilt optimization; cellular networks; antenna tilt; network optimization.;

   Sammanfattning : Antenna tilt is the angle subtended by the radiation beam and horizontal plane. This angle plays a vital role in determining the coverage and the interference of the network with neighbouring cells and adjacent base stations. LÄS MER