As 5G becomes more established and faces widespread roll-out, energy consumption of radio access networks around the globe will increase. Since the high-frequency radio waves used in 5G communication has a shorter effective range compared to the waves used in previous generations, 5G networks will require a higher number of radio units to compensate for their reduced range. Since the transmission of radio waves is a costly procedure in terms of energy consumption, this further increases the relevancy of radio equipment when considering solutions for increasing radio access networks' energy efficiency. This thesis has therefore provided a possible solution for increasing the energy efficiency of an O-RAN compliant radio access network by decreasing the energy consumption of its radio units. If a network's radio units are capable of entering a low-power sleep mode whenever they are left idle, i.e. not handling any traffic, the energy efficiency of a network can thus be increased by forcing its radio units to enter sleep mode as often as possible. This can be done by offloading traffic from radio units with little traffic onto other nearby radio units. The handovers required to perform such offloading, however, need to be predicted on the fly somewhere within the network. The solution proposed within this thesis therefore utilizes a component indigenous to the O-RAN architecture called RIC and its functionality-defining xApps which are capable of automatically detecting situations where radio units can be put to sleep as well as handling the offloading procedures. Through testing inside a simulated network, the set of xApps designed as a solution resulted in a potential 20-35% decrease in energy consumption among a radio access network's radio units.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:ltu-98204 |
Date | January 2023 |
Creators | Borg, Fredrik |
Publisher | Luleå tekniska universitet, Institutionen för system- och rymdteknik |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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