Unlock instant, AI-driven research and patent intelligence for your innovation.

Efficient 3d mobility support using reinforcement learning

A mobility, machine learning model technology, applied in wireless communication, electrical components, etc., to achieve the effect of improving robustness, reducing the number of handovers, and making efficient and flexible handover decisions

Pending Publication Date: 2022-08-02
TELEFON AB LM ERICSSON (PUBL)
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For example, existing mobility management processes struggle to provide robust mobility support for ubiquitous 3D coverage, especially for providing connectivity to low-altitude drones

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Efficient 3d mobility support using reinforcement learning
  • Efficient 3d mobility support using reinforcement learning
  • Efficient 3d mobility support using reinforcement learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0059] As mentioned above, certain challenges currently exist for three-dimensional (3D) mobility. For example, unlike terrestrial users, drones can move in any direction in three dimensions, can have arbitrary trajectories, and generally move faster than terrestrial users. Furthermore, base stations (BSs) are primarily designed to serve terrestrial users, and thus their antennas are downward sloping. Thus, the main lobe of the base station antenna covers a large part of the cell surface area to improve the performance of terrestrial user equipment (UE).

[0060] On the other hand, UAV UEs may be frequently served by side lobes of base station antennas with lower antenna gain. The coverage area of ​​the side lobes may be small, and the signal at the edges may drop sharply due to deep antenna nulls. At a given location, the strongest signal may come from a distant base station. Additionally, the side lobes of the base station may not fully cover the sky, resulting in coverag...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

According to some embodiments, a method performed by a network node for mobility management comprises obtaining data samples for modeling a wireless network environment comprising a plurality of cells, and constructing a machine learning model of the wireless network using the obtained data samples. A machine learning model is trained to determine a handover sequence of a wireless device among a plurality of cells to traverse the wireless device from a source cell to a destination cell. The method further includes receiving mobility information for the wireless device, determining one or more handover operations for the wireless device based on the mobility information, and transmitting the one or more handover operations to the wireless device.

Description

technical field [0001] Embodiments of the present disclosure are directed to wireless communications, and more particularly, to efficient three-dimensional (3D) mobility support using reinforcement learning. Background technique [0002] In general, all terms used herein are to be interpreted according to their ordinary meaning in the relevant technical field, unless a different meaning is explicitly given and / or implied from the context in which it is used. Unless expressly stated otherwise, all references to an (a / an) / the (the) element, device, component, component, step, etc. are to be construed open-ended as referring to that element, device, component, component , at least one instance of a step, etc. The steps of any method disclosed herein do not have to be performed in the exact order disclosed, unless a step is explicitly described as following or preceding another step, and / or where it is implied that a step must follow or precede another step. Any feature of any...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): H04W36/00
CPCH04W36/0055H04W36/0058H04W36/24H04W36/0083H04W36/322H04W36/32
Inventor 林兴钦陈赟T·罕M·莫扎法里
Owner TELEFON AB LM ERICSSON (PUBL)