A Linear Time Algorithm for the Optimal Discrete IRS Beamforming

It remains an open problem to find the optimal configuration of phase shifts under the discrete constraint for intelligent reflecting surface (IRS) in polynomial time. The above problem is widely believed to be difficult because it is not linked to any known combinatorial problems that can be solved...

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Vydané v:IEEE wireless communications letters Ročník 12; číslo 3; s. 1
Hlavní autori: Ren, Shuyi, Shen, Kaiming, Li, Xin, Chen, Xin, Luo, Zhi-Quan
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.03.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Approximation algorithms
Array signal processing
Beamforming
Big Data
Combinatorial analysis
Discrete beamforming for IRS/RIS
discrete quadratic program
global optimum
linear time algorithm
Optimization
Polynomials
Quadratic programming
Signal to noise ratio
Visualization
Wireless communication
ISSN:2162-2337, 2162-2345
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Shrnutí:It remains an open problem to find the optimal configuration of phase shifts under the discrete constraint for intelligent reflecting surface (IRS) in polynomial time. The above problem is widely believed to be difficult because it is not linked to any known combinatorial problems that can be solved efficiently. The branch-and-bound algorithms and the approximation algorithms constitute the best results in this area. Nevertheless, this work shows that the global optimum can actually be reached in linear time on average in terms of the number of reflective elements (REs) of IRS. The main idea is to geometrically interpret the discrete beamforming problem as choosing the optimal point on the unit circle. Although the number of possible combinations of phase shifts grows exponentially with the number of REs, it turns out that there are only a linear number of circular arcs that possibly contain the optimal point. Furthermore, the proposed algorithm can be viewed as a novel approach to a special case of the discrete quadratic program (QP).
Bibliografia:ObjectType-Article-1
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content type line 14
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2022.3232146