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Analysis of Intelligent Reflecting Surface-Assisted Multiple Access Schemes

Rahimi, Mohammad | 2023

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 56323 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Nasiri Kenari, Masoumeh; Ashtiani Mofrad Tehrani, Farid
  7. Abstract:
  8. In wireless multi-user networks, choosing the right multiple access method plays a significant role in providing services to users considering network constraints. On the other hand, Intelligent Reflecting Surfaces (IRS) is a new technology that significantly improves the performance of multiple access methods in wireless multi-user networks using a number of cost-effective elements. By adjusting the phase shift, IRS can improve the received signal power for users, enhance physical layer security, reduce base station power consumption, and provide better coverage for users. In this thesis, we examine a scenario with two single-antenna base stations and one passive IRS. Each base station provides service to its single-antenna users using non-orthogonal multiple access method. Initially, the achievable rates of users are determined by optimizing the phase shift of the IRS and power allocation of the base station with max-min objective. The calculation of the upper bound on achievable rates demonstrates the high accuracy of the proposed method. Furthermore, the achievable rates for users are determined in the case where the base stations have multiple antennas. To solve the problem of allocating IRS elements to base stations, a game model with pure strategie is introduced. By using the principle of indifference, the equilibrium point of this game is computed, and the power allocation is determined as the solution to the problem. Numerical results show that this method outperforms time-division multiple access (TDMA) method. Then, by modeling the problem of IRS allocation with a potential game model and calculating the equilibrium point, an optimal mechanism for allocating IRS elements to two base stations is obtained. This method outperforms TDMA and pure strategy game model in terms of the utility function of base stations. Finally, assuming IRS as a profit-seeking player and calculating the Stackelberg game equilibrium point, a mechanism is provided to evaluate the value of IRS elements and allocate them to base stations, along with power allocation. Numerical results demonstrate that this method outperforms uniform IRS pricing and without the presence of IRS
  9. Keywords:
  10. Non-Orthogonal Multiple Access ; Game Theory ; Achievable Rate Region ; Intelligent Reflective Surfaces ; Optimization

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