On Intelligent Reflecting Surfaces Element Allocation Using Genetic Algorithms
S Prabh - 2022 IEEE 33rd Annual International Symposium on …, 2022 - ieeexplore.ieee.org
2022 IEEE 33rd Annual International Symposium on Personal, Indoor …, 2022•ieeexplore.ieee.org
Intelligent reflecting surfaces (IRS) are surfaces consisting of an array of a large number of
passive but individually controlled reflecting elements. This paper explores the use of
genetic algorithms for optimal allocation of the reflecting elements in a multi-user setting. In
particular, it considers maximizing the sum-rate and equalizing the throughput in a wireless
environment consisting of multiple co-located IRSes. A real-coded genetic algorithm for
solving this problem is presented. Experimental results suggest that the method is effective.
passive but individually controlled reflecting elements. This paper explores the use of
genetic algorithms for optimal allocation of the reflecting elements in a multi-user setting. In
particular, it considers maximizing the sum-rate and equalizing the throughput in a wireless
environment consisting of multiple co-located IRSes. A real-coded genetic algorithm for
solving this problem is presented. Experimental results suggest that the method is effective.
Intelligent reflecting surfaces (IRS) are surfaces consisting of an array of a large number of passive but individually controlled reflecting elements. This paper explores the use of genetic algorithms for optimal allocation of the reflecting elements in a multi-user setting. In particular, it considers maximizing the sum-rate and equalizing the throughput in a wireless environment consisting of multiple co-located IRSes. A real-coded genetic algorithm for solving this problem is presented. Experimental results suggest that the method is effective.
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