Sökning: "Antennlutningsoptimering"

Hittade 3 uppsatser innehållade ordet Antennlutningsoptimering.

  1. 1. 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

  3. 2. Offline Reinforcement Learning for Remote Electrical Tilt Optimization : An application of Conservative Q-Learning

    Master-uppsats, KTH/Matematik (Avd.)

    Författare :Marcus Kastengren; [2021]
    Nyckelord :Remote Electrical Tilt; Antenna Tilt Optimization; Reinforcement Learning; Offline Reinforcement Learning; Conservative Q-Learning; Fjärrlutning; Antennlutningsoptimering; Förstärkningsinlärning; Offline-förstärkningsinlärning; Konservativ Q-inlärning;

    Sammanfattning : In telecom networks adjusting the tilt of antennas in an optimal manner, the so called remote electrical tilt (RET) optimization, is a method to ensure quality of service (QoS) for network users. Tilt adjustments made during operations in real-world networks are usually executed through a suboptimal policy, and a significant amount of data is collected during the execution of such policy. LÄS MER

  4. 3. Safe Reinforcement Learning for Remote Electrical Tilt Optimization

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

    Författare :Grigorios Iakovidis; [2021]
    Nyckelord :Remote Electrical Tilt; Antenna Tilt Optimization; Reinforcement Learning; SafeReinforcement Learning; Fjärrlutning; Antennlutningsoptimering; Förstärkningsinlärning; Säker Förstärkningsinlärning;

    Sammanfattning : The adjustment of the vertical tilt angle of Base Station (BS) antennas, also known as Remote Electrical Tilt (RET) optimization, is a simple and efficient method of optimizing modern telecommunications networks. Reinforcement Learning (RL) is a machine learning framework that can solve complex problems like RET optimization due to its capability to learn from experience and adapt to dynamic environments. LÄS MER