Distributed algorithms in signal processing chains for 5G radio access technology

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Journal ISSN

Volume Title

Perustieteiden korkeakoulu | Master's thesis

Date

2022-01-24

Department

Major/Subject

Computer Science

Mcode

SCI3042

Degree programme

Master’s Programme in Computer, Communication and Information Sciences

Language

en

Pages

87

Series

Abstract

Radio access technology (RAT) in 5G is a versatile and complex wireless communication system. Requirements of this technology include providing high throughput, assuring low latency communication, and guaranteeing high network capacity. In order to meet these requirements and simultaneously reduce deployment and operating costs, new concepts have been proposed in the recent times. These concepts transform 5G RAT implementation, called radio access network (RAN), into a highly distributed environment, and enable using RAN intelligent controllers. Therefore, new techniques are needed for managing 5G RAN as a distributed system deployed on different types of hardware. It is hypothesized that incorporating techniques from the distributed algorithms field may offer improved performance compared to centralized algorithms and help to decrease delays of the signal processing chains in RAN by efficiently utilizing available hardware resources. These improvements can be achieved by assigning functional blocks of the processing chains to available hardware resources in a way that minimizes a given cost function. To find an assignment with a minimal cost, one centralized technique and two distributed ones were investigated in this thesis. All three techniques were tested, using three random processing chains and three example processing chains from the 5G RAT area. The thesis evaluates the performance of these techniques and the quality of the obtained output. One of the proposed distributed algorithm offers the most appropriate balance between running time, memory utilization, and cost of the final assignment. However, additional work is needed to improve this solving technique and adapt it to real applications.

Description

Supervisor

Suomela, Jukka

Thesis advisor

Medeiros, Luiz

Keywords

distributed algorihtms, DCOP, ORAN, vRAN, optimalization, parallel computing

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