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Thanh Son Tran, "Study of IRS Assignment Strategies in Cooperative IRS-Aided Communication," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), August 2022. (Advisor: Anatolij Zubow; Referees: Falko Dressler and Thomas Sikora)


The further development of high-performance wireless communication is in progress since the demands have risen rapidly during the last few years. Intelligent reflecting surface (IRS) is a new promising and transformative technology with great potential for enhancing future wireless networks. Investigating the impact of the IRSs will open up new opportunities to meet the stringent requirements. Simulation provides the fundamentals for achieving new insights; thus, we have proposed a scalable simulation environment, including the implementation in MATLABĀ®. The simulation is built on mathematical models presented in prior works. The simulation results proved the performance gain of an IRS-aided network since the beamforming gain provided by the smartly configured reflective elements could partly compensate for the path loss. However, a significant benefit of an IRS-aided network could only be achieved when the direct links suffer under Non-line-of-sight (NLOS) propagation. Additionally, the Line-of-sight (LOS) communication for the inter-IRS links is required since the path loss would dominate otherwise. Moreover, it is necessary to deploy a large number of reflecting elements for a significant performance gain. In addition, the performance will be pushed further by increasing the number of IRSs. The simulation results have also shown that maximizing the beamforming gain is inferior compared to minimizing path loss. Regarding parallel communication with multiple- user, it has turned out that prioritizing users, which have the lowest link quality, is advantageous when it comes to improving the average network performance.

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Thanh Son Tran

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    author = {Tran, Thanh Son},
    title = {{Study of IRS Assignment Strategies in Cooperative IRS-Aided Communication}},
    advisor = {Zubow, Anatolij},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {8},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Bachelor Thesis},
    year = {2022},

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