MIMO QRadRCom: A New Topology for Quantum-Assisted Radar and Relay-Based MIMO System

The proposal outlines the design of a radar and relay-assisted communication system with multiple input multiple output (MIMO) configuration, utilizing quantum algorithm in coexistence scenario. We name it MIMO QRadRCom framework. Quantum computation offers significant speed-ups and holds promise for future technologies like sixth generation (6G) cellular networks. By integrating quantum simulation, we aim to design parameters, like an equalizer at the communication receiver and others, and then classically optimize the rest of the design parameters. The equalizer comes from the linear minimum mean square error (LMMSE) criterion, which involves matrix inversion and is classically expensive. The mathematical formulations address classical and quantum inaccuracies, supported by numerical simulations on the IBM quantum machine.

Authors

Institutions

Publication Details

Journal
IEEE Communications Letters
Published
2024-10-02
DOI
https://doi.org/10.1109/lcomm.2024.3472497
Primary Topic
Advanced MIMO Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

MIMO QRadRCom: A New Topology for Quantum-Assisted Radar and Relay-Based MIMO System

Amit Kumar Dutta, Mostafizur Rahaman Laskar, Soumita Naskar
IEEE Communications Letters
Advanced MIMO Systems Optimization
article

MIMO QRadRCom: A New Topology for Quantum-Assisted Radar and Relay-Based MIMO System

Amit Kumar Dutta, Mostafizur Rahaman Laskar, Soumita Naskar
article en

Abstract

The proposal outlines the design of a radar and relay-assisted communication system with multiple input multiple output (MIMO) configuration, utilizing quantum algorithm in coexistence scenario. We name it MIMO QRadRCom framework. Quantum computation offers significant speed-ups and holds promise for future technologies like sixth generation (6G) cellular networks. By integrating quantum simulation, we aim to design parameters, like an equalizer at the communication receiver and others, and then classically optimize the rest of the design parameters. The equalizer comes from the linear minimum mean square error (LMMSE) criterion, which involves matrix inversion and is classically expensive. The mathematical formulations address classical and quantum inaccuracies, supported by numerical simulations on the IBM quantum machine.

IEEE Communications LettersVol. 28(11)
Indian Institute of Technology Kharagpur (IN)
Affordable and clean energy
Openalex Percentile: Top 85%
Advanced MIMO Systems Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

MIMO QRadRCom: A New Topology for Quantum-Assisted Radar and Relay-Based MIMO System — Amit Kumar Dutta, Mostafizur Rahaman Laskar, et al. · IEEE Communications Letters (2024) | TGRS Research Map | TGRS