Sökning: "wireless prediction"

Visar resultat 1 - 5 av 38 uppsatser innehållade orden wireless prediction.

1. 1. AI Enabled Cloud RAN Test Automation : Automatic Test Case Prediction Using Natural Language Processing and Machine Learning Techniques

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

   Författare :Jeet Santosh Nimbhorkar; [2023]
   Nyckelord :Test Automation; Natural Language Processing; Machine Learning; Keyword Extraction; Prediction; Testautomatisering; Naturlig Språkbehandling; Maskininlärning; Nyckelord Extraktion; Förutsägelse;

   Sammanfattning : The Cloud Radio Access Network (RAN) is a technology used in the telecommunications industry. It provides a flexible, scalable, and costeffective solution for managing and delivering seamless wireless network services. LÄS MER

3. 2. Test Case Selection from Test Specifications using Natural Language Processing

   Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

   Författare :Alok Gupta; [2023]
   Nyckelord :Cloud RAN; Telecommunication; Test Automation; Artificial Intelligence; Machine Learning; Natural Language Processing; Keyword Extraction; Prediction;

   Sammanfattning : The Cloud Radio Access Network (RAN) is a groundbreaking technology employed in the telecommunications industry, offering flexible, scalable, and cost-effective solutions for seamless wireless network services. However, testing Cloud RAN applications presents significant challenges due to their complexity, potentially leading to delays and increased costs. LÄS MER

4. 3. Personalized Federated Learning for mmWave Beam Prediction Using Non-IID Sub-6 GHz Channels

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

   Författare :Yuan Cheng; [2022]
   Nyckelord :Personalized Federated Learning; Millimeter wave; Beamforming; DeepMIMO; Non-IID; Personaliserad Federad Inlärning; Millimetervågor; Strålformning; DeepMIMO; Icke-IID;

   Sammanfattning : While it is difficult for base stations to estimate the millimeter wave (mmWave) channels and find the optimal mmWave beam for user equipments (UEs) quickly, the sub-6 GHz channels which are usually easier to obtain and more robust to blockages could be used to reduce the time before initial access and enhance the reliability of mmWave communication. Considering that the channel information is collected by a massive number of radio base stations and would be sensitive to privacy and security, Federated Learning (FL) is a match for this use case. LÄS MER

5. 4. Energy Consumptions for Vehicles using Multitask Learning

   Master-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Venkata Sai Vivek Uddagiri; Shankara Narayanan Bangalore Ramalingam; [2022]
   Nyckelord :;

   Sammanfattning : This thesis aims to predict energy (fossil fuel and electric) consumption of internal combustion and hybrid vehicles. This thesis is in association with Wireless cars. Accurate prediction of energy consumption in vehicles is vital, as it can pave the way for a more sustainable future. LÄS MER

7. 5. ML-Aided Cross-Band Channel Prediction in MIMO Systems

   Master-uppsats, Linköpings universitet/Statistik och maskininlärning

   Författare :Alejo Pérez Gómez; [2022]
   Nyckelord :MIMO; Deep Learning; Machine Learning; Probabilistic Principal Component Analysis; Variational Autoencoder;

   Sammanfattning : Wireless communications technologies have experienced an exponential development during the last decades. 5G is a prominent exponent whose one of its crucial component is the Massive MIMO technology. LÄS MER