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Optimization of 5G New Radio for Fixed Wireless Access
Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering.
2019 (English)Independent thesis Advanced level (professional degree), 300 HE creditsStudent thesis
Abstract [en]

With the advent of new 5G networks, the interest in connecting house-hold to the Internet via mobile networks has increased. One such way toconnect users is using completely stationary antennas. This use-case iscalled Fixed Wireless Access (FWA) and is seen as promising, cost-efficient means of expanding internet connectivity. Stationary users connected at high frequencies, such as 28 GHz, leads to a special use-case and environment for 5G New Radio (NR). This thesis investigates the characteristics of these FWA deployments and the control signaling on the physical layer of NR. The overhead and feasibility of eachsignal is considered. A FWA deployment in the 28 GHz band with 64 users is simulated with different line-of-sight settings and receiver placements. It is concluded that direct line-of-sight to the base station is vital for high user and cell throughput and that there are significant drawbacks of placing the receiver indoors. New algorithms for Channel State Information Reference Signal (CSI-RS) transmission for both beam management and link adaptation are proposed and evaluated. The beam management algorithms do not displayany significant performance gains over the default sweeping algorithm. Closer investigation of simulation results shows that several beams can have almost equal signal strength with the chosen antenna set up, minimizing potential gains of quickly adapting to environmental changes. Results show there are clear benefits of using an aperiodic and adaptive transmission scheme for CSI-RS transmissions over a fixed-rate transmission scheme, yielding a 7% increase in user goodput at similar levels of overhead.

Place, publisher, year, edition, pages
2019. , p. 73
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:ltu:diva-76077OAI: oai:DiVA.org:ltu-76077DiVA, id: diva2:1353201
External cooperation
Ericsson Research
Subject / course
Student thesis, at least 30 credits
Educational program
Computer Science and Engineering, master's level
Presentation
2019-06-06, 10:00 (English)
Supervisors
Examiners
Available from: 2019-10-09 Created: 2019-09-20 Last updated: 2019-10-09Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • en-US
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Output format
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