Performance of XR in 5G industrial networks
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Sähkötekniikan korkeakoulu |
Master's thesis
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Authors
Date
2023-10-09
Department
Major/Subject
Communications Engineering
Mcode
ELEC3029
Degree programme
CCIS - Master’s Programme in Computer, Communication and Information Sciences (TS2013)
Language
en
Pages
71
Series
Abstract
Augmented Reality (AR) has been defined as one of the main enablers of the Fourth Industrial Revolution, the use of AR helps to optimize the production in a factory. AR contemplates the use of overly complex tasks and algorithms to make it possible for the users to visualize the AR virtual content onto the real world. The use of wireless Head-Mounted Displays (HMDs) facilitates AR in a factory environment. However, the latency requirements for AR applications are certainly tight, and executing these complex tasks in an HMD will increase the processing time and thus the end-to-end latency. To solve this problem, some of the AR functionalities can be executed in a powerful server at the Multi-Access Edge Computing (MEC). The offloading, or execution, of these tasks in a server, located at the edge of the network, requires that the AR HMD is connected to the 5G network. The performance of the AR application in the 5G RAN is limited by the characteristics of the AR video traffic, this traffic is composed of large packets of alternating size. In indoor scenarios, the performance is also affected by the strong interference in downlink. The interference, in addition to the gigantic packets of data, are the main cause for downgraded performance. This thesis proposes three cases for offloading a few AR functionalities to a MEC node. Furthermore, the thesis assesses the performance of the AR offloading cases based on the latency and the number of satisfied users in the network. The evaluation is done using a system-level simulator, for the three offloading cases. It is demonstrated that for an interference-limited scenario, using a high initial Block Error Rate (BLER), for the transmission of AR video traffic, allows the network to better adapt to the channel conditions. The Interference Rejection Combining (IRC) receiver with 4 RX antenna ports at the user, enhances the system capacity significantly. Finally, it is also shown that under the current 5G system, using Configured Grant (CG) for pose traffic is the best solution to reach the notably tight latency requirements for pose traffic.Description
Supervisor
Mähönen, PetriThesis advisor
Del Carpio, Luis FelipeKeywords
augmented reality, 5G, MEC, configured grant, Industry 4.0