Sökning: "cell reinforcement"

Visar resultat 1 - 5 av 20 uppsatser innehållade orden cell reinforcement.

1. 1. Mobile Traffic Classification and Multi-Cell Base Station Control for Energy-Efficient 5G Networks

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

   Författare :Cai Tianzhang; [2023]
   Nyckelord :;

   Sammanfattning : The global energy consumption of mobile networks is rapidly increasing due to the exponential growth of mobile network traffic. The advent of next-generation cellular technologies such as fifth-generation (5G) and beyond promises higher network throughput and lower latency but also demands higher power consumption for its denser base station (BS) deployment and more energy-intensive processors. LÄS MER

3. 2. Characterization of Kelvin Cell Cored Sandwich Structures with Analysis and Experiments

   Master-uppsats, KTH/Lättkonstruktioner, marina system, flyg- och rymdteknik, rörelsemekanik

   Författare :Sabahattin Bora Günay; [2023]
   Nyckelord :Kelvin Cell; Sandwich Structure; Space Structures; Three Point Bending Test; Structural Stiffness; Kelvin-cell; smörgåsstruktur; rymdstrukturer; trepunktsböjningstest; strukturell styvhet;

   Sammanfattning : In order to satisfy the mechanical requirements for space structures, achieving lightweight designs is of the greatest significance. The primary focus of this study is the utilization of Kelvin cell core in the design of sandwich structures for space applications. LÄS MER

4. 3. Improving Co-existence of URLLC and Distributed AI using RL

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

   Författare :Wei Shi; [2023]
   Nyckelord :5G; URLLC; RL; HRL; Optimization; 5G; URLLC; RL; HRL; Optimering;

   Sammanfattning : In 5G, Ultra-reliable and low-Latency communications (URLLC) service is envisioned to enable use cases with strict reliability and latency requirements on wireless communication. For the upcoming 6G network, machine learning (ML) also stands an important role that introduces intelligence and further enhances the system performance. LÄS MER

5. 4. Link Adaptation in 5G Networks : Reinforcement Learning Framework based Approach

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

   Författare :Siva Satya Sri Ganesh Seeram; [2022]
   Nyckelord :Link Adaptation; OLLA; AMC; Reinforcement Learning; DDPG; BLER; Länkanpassning; OLLA; AMC; förstärkningsinlärning; DDPG; BLER;

   Sammanfattning : Link Adaptation is a core feature introduced in gNodeB (gNB) for Adaptive Modulation and Coding (AMC) scheme in new generation cellular networks. The main purpose of this is to correct the estimated Signal-to-Interference-plus-Noise ratio (SINR) at gNB and select the appropriate Modulation and Coding Scheme (MCS) so the User Equipment (UE) can decode the data successfully. LÄS MER

7. 5. Access Point Selection and Clustering Methods with Minimal Switching for Green Cell-Free Massive MIMO Networks

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

   Författare :Qinglong He; [2022]
   Nyckelord :Cell-free massive MIMO; multi-objective optimization; deep reinforcement learning; AP switch ON OFF; energy efficiency; Cellfri massiv MIMO; multiobjektiv optimering; djup förstärkningsinlärning; AP switch ON OFF; energieffektivitet;

   Sammanfattning : As a novel beyond fifth-generation (5G) concept, cell-free massive MIMO (multiple-input multiple-output) recently has become a promising physical-layer technology where an enormous number of distributed access points (APs), coordinated by a central processing unit (CPU), cooperate to coherently serve a large number of user equipments (UEs) in the same time/frequency resource. However, denser AP deployment in cell-free networks as well as an exponentially growing number of mobile UEs lead to higher power consumption. LÄS MER