Essays about: "BASE STATION"

Showing result 16 - 20 of 310 essays containing the words BASE STATION.

  1. 16. Beam-steered Modulation in Advanced Antenna System

    University essay from Lunds universitet/Institutionen för elektro- och informationsteknik

    Author : Smitha Jinnahalli Venugopal; [2023]
    Keywords : 5G-MIMO; Beam-forming; Beam-steering; Advanced antenna systems; Technology and Engineering;

    Abstract : The newer spectral bands in millimeter-wave (mm-Wave) spectrum over the last few years have made higher data rates possible and improved quality of service for the users, but it possesses new challenges to design spectral agile radios. Power Amplifiers (PA) are a crucial analog component connected to Multiple input multiple output (MIMO) antennas which inherits non-linear effects. READ MORE

  2. 17. Improving the Robustness of Over-the-Air Synchronization for 5G Networks in a Multipath Environment

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Anders Erninger; [2023]
    Keywords : Peak selection algorithms; Peak matching; Time alignment error; Over-the-air synchronization; Multipath environment; Toppvalsalgoritmer; Toppmatchning; Tidsfel; Luftburen synkronisation; Flervägsmiljö;

    Abstract : Synchronization between base stations is a fundamental part of any operating telecommunication system. With 5G and future generations of mobile networks, the data speeds are getting higher, which creates the need for fast and accurate synchronization. In wireless systems, the transmitted signals are affected by the environment. READ MORE

  3. 18. INVESTIGATING THE TOXIC AND ACIDIFYING EFFECT OF SCRUBBER EFFLUENT ON STRONGYLOCENTROTUS DROEBACHIENSIS LARVAE

    University essay from Göteborgs universitet / Instiutionen för biologi och miljövetenskap

    Author : Ida Vartia; [2022-09-28]
    Keywords : ;

    Abstract : To meet the new environmental requirements of reduced sulfur emissions from ships, many shipowners have installed an open-loop scrubber to clean the exhaust. In this scrubbing process, seawater is pumped from the ocean and combined with the emission gas, creating an acidic and toxic effluent that is directly discharged into the ocean, potentially damaging the marine environment. READ MORE

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

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

    Abstract : 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. READ MORE

  5. 20. Hybrid Deep Learning Model for Cellular Network Traffic Prediction : Case Study using Telecom Time Series Data, Satellite Imagery, and Weather Data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Ali Shibli; [2022]
    Keywords : Cellular network traffic; multi-modal; satellite imagery; weather data; LSTM; CNN; time series; Trafic sur les réseaux cellulaires; multimodal; imagerie satellite; données météo; LSTM; CNN; séries temporelles; Förutsägelse av mobilnätstrafik; multimodal modell; satellitbilder; väderdata; LSTM; CNN; tidsseriein;

    Abstract : Cellular network traffic prediction is a critical challenge for communication providers, which is important for use cases such as traffic steering and base station resources management. Traditional prediction methods mostly rely on historical time-series data to predict traffic load, which often fail to model the real world and capture surrounding environment conditions. READ MORE