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Quantum Computing for MIMO Beam Selection Problem: Model and Optical Experimental Solution
Networking and Internet Architecture · Submitted 19 Oct 2023
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim The results demonstrate an average performance improvement by a factor of 261.23 and 20.6, respectively, which shows that CIM-based solution performs significantly better in terms of selecting the optimal subset of beams.
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The abstract, sentence by sentence
Massive multiple-input multiple-output (MIMO) has gained widespread popularity in recent years due to its ability to increase data rates, improve signal quality, and provide better coverage in challenging environments. In this paper, we investigate the MIMO beam selection (MBS) problem, which is proven to be NP-hard and computationally intractable. To deal with this problem, quantum computing that can provide faster and more efficient solutions to large-scale combinatorial optimization is considered. MBS is formulated in a quadratic unbounded binary optimization form and solved with Coherent Ising Machine (CIM) physical machine. We compare the performance of our solution with two classic heuristics, simulated annealing and Tabu search. The results demonstrate an average performance improvement by a factor of 261.23 and 20.6, respectively, which shows that CIM-based solution performs significantly better in terms of selecting the optimal subset of beams. This work shows great promise for practical 5G operation and promotes the application of quantum computing in solving computationally hard problems in communication.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Massive multiple-input multiple-output (MIMO) has gained widespread popularity in recent years due to its ability to increase data rates, improve signal quality, and provide better coverage in challenging environments. | background 1.00 | 0.04 | 0.02 | asserted 1.00 |
| s1 | In this paper, we investigate the MIMO beam selection (MBS) problem, which is proven to be NP-hard and computationally intractable. | background 0.58 | 0.26 | 0.03 | asserted 1.00 |
| s2 | To deal with this problem, quantum computing that can provide faster and more efficient solutions to large-scale combinatorial optimization is considered. | method 0.48 | 0.11 | 0.03 | hedged possibility 0.62 |
| s3 | MBS is formulated in a quadratic unbounded binary optimization form and solved with Coherent Ising Machine (CIM) physical machine. | method 0.99 | 0.91 | 0.05 | asserted 1.00 |
| s4 | We compare the performance of our solution with two classic heuristics, simulated annealing and Tabu search. | method 0.91 | 0.91 | 0.03 | asserted 0.81 |
| s5 | The results demonstrate an average performance improvement by a factor of 261.23 and 20.6, respectively, which shows that CIM-based solution performs significantly better in terms of selecting the optimal subset of beams. | result 0.99 | 0.95 | 0.66 | asserted 1.00 |
| s6 | This work shows great promise for practical 5G operation and promotes the application of quantum computing in solving computationally hard problems in communication. | interpretation 0.98 | 0.38 | 0.62 | asserted 0.71 |
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The paper
Original abstract
Massive multiple-input multiple-output (MIMO) has gained widespread popularity in recent years due to its ability to increase data rates, improve signal quality, and provide better coverage in challenging environments. In this paper, we investigate the MIMO beam selection (MBS) problem, which is proven to be NP-hard and computationally intractable. To deal with this problem, quantum computing that can provide faster and more efficient solutions to large-scale combinatorial optimization is considered. MBS is formulated in a quadratic unbounded binary optimization form and solved with Coherent Ising Machine (CIM) physical machine. We compare the performance of our solution with two classic heuristics, simulated annealing and Tabu search. The results demonstrate an average performance improvement by a factor of 261.23 and 20.6, respectively, which shows that CIM-based solution performs significantly better in terms of selecting the optimal subset of beams. This work shows great promise for practical 5G operation and promotes the application of quantum computing in solving computationally hard problems in communication.
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How the literature uses it
2 arXiv papers cite this in 2 sentences
Papers citing it · 1 sentence without a confident label
Cites it as background 1 paper
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The application of physics-inspired quantum computing architectures and algorithms in wireless communication systems is a new research area of paramount importance [ref] .
Optimizing Configuration Selection in Reconfigurable-Antenna MIMO Systems: Physics-Inspired Heuristic Solvers · Introduction · 0.89
What it cites
Cites as background 1 paper
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Two types of DOPO-based approaches have been developed, which are the optical delay lines CIM [ref] and the measurement feedback CIM [ref] .
A coherent Ising machine for MAX-CUT problems : Performance evaluation against semidefinite programming relaxation and simulated annealing · Experimental Results—Comparision between CIM physical machine and classic heuristics · 0.90
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