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Quantum Decoding of Error Correction Codes for Wireless Networks
Quantum Decoding of Error Correction Codes for Wireless Networks
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211152809
- ISBN
- 9798384463948
- DDC
- 004
- 서명/저자
- Quantum Decoding of Error Correction Codes for Wireless Networks
- 발행사항
- [Sl] : Princeton University, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 203 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 86-04, Section: B.
- 주기사항
- Advisor: Jamieson, Kyle.
- 학위논문주기
- Thesis (Ph.D.)--Princeton University, 2024.
- 초록/해제
- 요약Error correction codes are essential for reliability and capacity in wireless networks. By correcting errors in real-time, they reduce re-transmissions, conserve bandwidth, and enhance network performance. However, these advantages come at the price of high decoding complexity and high latency which compels network designers to make sub-optimal deployment choices such as considering approximate decoding algorithms, limiting parallelism, bit-precision, and iteration counts, sacrificing the potential capacity and performance gains. Moreover, the ever-increasing user demand in wireless networks poses additional challenges in managing power consumption, operational costs, and the carbon footprint of base stations and terminals. This highlights the need for continued innovation in wireless network baseband architecture and implementation strategies.This dissertation introduces quantum computing-based processing architectures for decoding error correction codes, offering new computational paradigms to address these challenges at scale. By harnessing the principles of quantum mechanics, we propose a transformative shift in the way decoding is achieved, benefiting wireless performance and capacity, through the design and implementation of the following systems: (1) QBP, quantum annealing decoder for LDPC codes, (2) HyPD, hybrid classical-quantum annealing decoder for Polar codes, (3) QGateD, quantum amplitude amplification decoder for generic XOR-based error correction codes, (4) FDeQ, quantum gate decoder flexible to both LDPC and Polar codes, (5) QAVP, quantum annealing approach to vector perturbation precoding (a multi-user MIMO downlink baseband optimization problem). These systems collectively fall under the thesis that quantum computing is a promising approach for baseband processing, warranting further justification from an economic and environmental impact perspective. To address this and to make the case for quantum computing in wireless industry, (6) the dissertation presents a comprehensive cost and carbon footprint analysis of quantum hardware, both quantitatively and qualitatively. This may be of potential interest to NextG wireless networks and quantum architectures.
- 일반주제명
- Computer science
- 일반주제명
- Engineering
- 일반주제명
- Information technology
- 일반주제명
- Computational physics
- 키워드
- Decoding
- 키워드
- Embedding
- 키워드
- Optimization
- 기타저자
- Princeton University Computer Science
- 기본자료저록
- Dissertations Abstracts International. 86-04B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■00520250211152809
■006m o d
■007cr#unu||||||||
■020 ▼a9798384463948
■035 ▼a(MiAaPQ)AAI31557685
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a004
■1001 ▼aKasi, Sai Srikar.▼0(orcid)0000-0001-6519-9688
■24510▼aQuantum Decoding of Error Correction Codes for Wireless Networks
■260 ▼a[Sl]▼bPrinceton University▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a203 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 86-04, Section: B.
■500 ▼aAdvisor: Jamieson, Kyle.
■5021 ▼aThesis (Ph.D.)--Princeton University, 2024.
■520 ▼aError correction codes are essential for reliability and capacity in wireless networks. By correcting errors in real-time, they reduce re-transmissions, conserve bandwidth, and enhance network performance. However, these advantages come at the price of high decoding complexity and high latency which compels network designers to make sub-optimal deployment choices such as considering approximate decoding algorithms, limiting parallelism, bit-precision, and iteration counts, sacrificing the potential capacity and performance gains. Moreover, the ever-increasing user demand in wireless networks poses additional challenges in managing power consumption, operational costs, and the carbon footprint of base stations and terminals. This highlights the need for continued innovation in wireless network baseband architecture and implementation strategies.This dissertation introduces quantum computing-based processing architectures for decoding error correction codes, offering new computational paradigms to address these challenges at scale. By harnessing the principles of quantum mechanics, we propose a transformative shift in the way decoding is achieved, benefiting wireless performance and capacity, through the design and implementation of the following systems: (1) QBP, quantum annealing decoder for LDPC codes, (2) HyPD, hybrid classical-quantum annealing decoder for Polar codes, (3) QGateD, quantum amplitude amplification decoder for generic XOR-based error correction codes, (4) FDeQ, quantum gate decoder flexible to both LDPC and Polar codes, (5) QAVP, quantum annealing approach to vector perturbation precoding (a multi-user MIMO downlink baseband optimization problem). These systems collectively fall under the thesis that quantum computing is a promising approach for baseband processing, warranting further justification from an economic and environmental impact perspective. To address this and to make the case for quantum computing in wireless industry, (6) the dissertation presents a comprehensive cost and carbon footprint analysis of quantum hardware, both quantitatively and qualitatively. This may be of potential interest to NextG wireless networks and quantum architectures.
■590 ▼aSchool code: 0181.
■650 4▼aComputer science
■650 4▼aEngineering
■650 4▼aInformation technology
■650 4▼aComputational physics
■653 ▼aDecoding
■653 ▼aEmbedding
■653 ▼aError correction codes
■653 ▼aOptimization
■653 ▼aQuantum computing
■690 ▼a0984
■690 ▼a0489
■690 ▼a0537
■690 ▼a0216
■71020▼aPrinceton University▼bComputer Science.
■7730 ▼tDissertations Abstracts International▼g86-04B.
■790 ▼a0181
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17163920▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
