Intelligent Reflecting Surface (IRS) Allocation Scheduling Method Using Combinatorial Optimization by Quantum Computing

Takahiro Ohyama, Yuichi Kawamoto, Nei Kato

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)


Intelligent Reflecting Surface (IRS) significantly improves the energy utilization efficiency in 6th generation cellular communication systems. Here, we consider a system with multiple IRS and users, with one user communicating via several IRSs. In such a system, the user to which an IRS is assigned for each unit time must be determined to realize efficient communication. The previous studies on the optimization of various parameters for IRS based wireless systems did not consider the optimization of such IRS allocation scheduling. Therefore, we propose an IRS allocation scheduling method that limits the number of users who allocate each IRS to one unit time and sets the reflection coefficients of the IRS specifically to the assigned user resulting in the maximum IRS array gain. Additionally, as the proposed method is a combinatorial optimization problem, we develop a quadratic unconstrained binary optimization formulation to solve this using quantum computing. This will lead to the optimization of the entire system at a high speed and low power consumption in the future. Using computer simulation, we clarified that the proposed method realizes a more efficient communication compared to the method where one IRS is simultaneously used by multiple users.

Original languageEnglish
Pages (from-to)1633-1644
Number of pages12
JournalIEEE Transactions on Emerging Topics in Computing
Issue number3
Publication statusPublished - 2022


  • IRS allocation scheduling
  • Intelligent reflecting surface
  • combinatorial optimization
  • quantum annealing
  • quantum computing

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Information Systems
  • Human-Computer Interaction
  • Computer Science Applications


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