Regularized Ising Formulation for Near-Optimal MIMO Detection using Quantum Inspired Solvers

Abhishek Kumar Singh; Kyle Jamieson; Peter L. McMahon; Davide Venturelli

doi:10.1109/GLOBECOM48099.2022.10001657

Regularized Ising Formulation for Near-Optimal MIMO Detection using Quantum Inspired Solvers

Abhishek Kumar Singh, Kyle Jamieson, Peter L. McMahon, Davide Venturelli

Research output: Contribution to journal › Conference article › peer-review

2 Scopus citations

Abstract

Optimal MIMO detection is one of the most computationally challenging tasks in wireless systems. We show that the quantum-inspired computing approach based on Coherent Ising Machines (CIMs) is a promising candidate for performing near-optimal MIMO detection. We propose a novel regularized Ising formulation for MIMO detection that mitigates a common error floor issue in the direct approach adopted in the existing literature on MIMO detection using Quantum Annealing. We evaluate our methods using a simplified, quantum-inspired model and show that our methods can achieve a near-optimal performance for several Large MIMO systems, like 16times 16,20times 20, and 24times 24 MIMO with BPSK modulation.

Original language	English (US)
Pages (from-to)	2517-2522
Number of pages	6
Journal	Proceedings - IEEE Global Communications Conference, GLOBECOM
DOIs	https://doi.org/10.1109/GLOBECOM48099.2022.10001657
State	Published - 2022
Event	2022 IEEE Global Communications Conference, GLOBECOM 2022 - Rio de Janeiro, Brazil Duration: Dec 4 2022 → Dec 8 2022

All Science Journal Classification (ASJC) codes

Signal Processing
Hardware and Architecture
Computer Networks and Communications
Artificial Intelligence

Keywords

Coherent Ising machines
Large MIMO
MIMO detection
Physics-inspired Ising machine-based computation
Quantum inspired solvers

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10.1109/GLOBECOM48099.2022.10001657

Cite this

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title = "Regularized Ising Formulation for Near-Optimal MIMO Detection using Quantum Inspired Solvers",

abstract = "Optimal MIMO detection is one of the most computationally challenging tasks in wireless systems. We show that the quantum-inspired computing approach based on Coherent Ising Machines (CIMs) is a promising candidate for performing near-optimal MIMO detection. We propose a novel regularized Ising formulation for MIMO detection that mitigates a common error floor issue in the direct approach adopted in the existing literature on MIMO detection using Quantum Annealing. We evaluate our methods using a simplified, quantum-inspired model and show that our methods can achieve a near-optimal performance for several Large MIMO systems, like 16times 16,20times 20, and 24times 24 MIMO with BPSK modulation.",

keywords = "Coherent Ising machines, Large MIMO, MIMO detection, Physics-inspired Ising machine-based computation, Quantum inspired solvers",

author = "Singh, \{Abhishek Kumar\} and Kyle Jamieson and McMahon, \{Peter L.\} and Davide Venturelli",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE Global Communications Conference, GLOBECOM 2022 ; Conference date: 04-12-2022 Through 08-12-2022",

year = "2022",

doi = "10.1109/GLOBECOM48099.2022.10001657",

language = "English (US)",

pages = "2517--2522",

journal = "Proceedings - IEEE Global Communications Conference, GLOBECOM",

issn = "2334-0983",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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T1 - Regularized Ising Formulation for Near-Optimal MIMO Detection using Quantum Inspired Solvers

AU - Singh, Abhishek Kumar

AU - Jamieson, Kyle

AU - McMahon, Peter L.

AU - Venturelli, Davide

PY - 2022

Y1 - 2022

N2 - Optimal MIMO detection is one of the most computationally challenging tasks in wireless systems. We show that the quantum-inspired computing approach based on Coherent Ising Machines (CIMs) is a promising candidate for performing near-optimal MIMO detection. We propose a novel regularized Ising formulation for MIMO detection that mitigates a common error floor issue in the direct approach adopted in the existing literature on MIMO detection using Quantum Annealing. We evaluate our methods using a simplified, quantum-inspired model and show that our methods can achieve a near-optimal performance for several Large MIMO systems, like 16times 16,20times 20, and 24times 24 MIMO with BPSK modulation.

AB - Optimal MIMO detection is one of the most computationally challenging tasks in wireless systems. We show that the quantum-inspired computing approach based on Coherent Ising Machines (CIMs) is a promising candidate for performing near-optimal MIMO detection. We propose a novel regularized Ising formulation for MIMO detection that mitigates a common error floor issue in the direct approach adopted in the existing literature on MIMO detection using Quantum Annealing. We evaluate our methods using a simplified, quantum-inspired model and show that our methods can achieve a near-optimal performance for several Large MIMO systems, like 16times 16,20times 20, and 24times 24 MIMO with BPSK modulation.

KW - Coherent Ising machines

KW - Large MIMO

KW - MIMO detection

KW - Physics-inspired Ising machine-based computation

KW - Quantum inspired solvers

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U2 - 10.1109/GLOBECOM48099.2022.10001657

DO - 10.1109/GLOBECOM48099.2022.10001657

M3 - Conference article

AN - SCOPUS:85146916978

SN - 2334-0983

SP - 2517

EP - 2522

JO - Proceedings - IEEE Global Communications Conference, GLOBECOM

JF - Proceedings - IEEE Global Communications Conference, GLOBECOM

T2 - 2022 IEEE Global Communications Conference, GLOBECOM 2022

Y2 - 4 December 2022 through 8 December 2022

ER -

Regularized Ising Formulation for Near-Optimal MIMO Detection using Quantum Inspired Solvers

Abstract

All Science Journal Classification (ASJC) codes

Keywords

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