Sökning: "Coverage and Capacity Optimization"
Visar resultat 1 - 5 av 11 uppsatser innehållade orden Coverage and Capacity Optimization.
1. Digital Front End Algorithms for Sub-Band Full Duplex
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : Sub-band full duplex is a new communication scheme technology, where a single frequency band is partitioned into sub-bands for downlink (DL) and up-link(UL) transmissions, and both can take place simultaneously. The idea behind the sub-band full duplex development is to improve the throughput, and coverage and reduce the latency of the UL communication by allowing the UL reception during the DL transmission. LÄS MER
2. Model-based Residual Policy Learning for Sample Efficient Mobile Network Optimization
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)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
3. Optimizing the locations of bike-sharing stations using GPS-based trip data: A Spatio-temporal demand coverage approach
Master-uppsats, Lunds universitet/Institutionen för naturgeografi och ekosystemvetenskapSammanfattning : Shared micro-mobility services are increasingly embraced by cities around the world in recent years. Their benefits over other transportation modes in certain frames encourage traffic/urban planners, public authorities to establish such systems in urban areas. LÄS MER
4. Bayesian Off-policy Sim-to-Real Transfer for Antenna Tilt Optimization
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Choosing the correct angle of electrical tilt in a radio base station is essential when optimizing for coverage and capacity. A reinforcement learning agent can be trained to make this choice. If the training of the agent in the real world is restricted or even impossible, alternative methods can be used. LÄS MER
5. Machine learning based call drop healing in 5G
Master-uppsats, Lunds universitet/Institutionen för elektro- och informationsteknikSammanfattning : Self-Organizing Network (SON) functions include self-configuration, dynamic optimization and self-healing of networks. In the era of 5G, mobile operators are increasingly exploring areas of SON through Machine Learning (ML) techniques. LÄS MER