TR2022-052

Variational Quantum Compressed Sensing for Joint User and Channel State Acquisition in Grant-Free Device Access Systems

Abstract:

This paper introduces a new quantum computing framework integrated with a two-step compressed sensing technique, applied to a joint channel estimation and user identification problem. We propose a variational quantum circuit (VQC) design as a new denoising solution. For a practical grant-free communications system having correlated device activities, variational quantum parameters for Pauli rotation gates in the proposed VQC system are optimized to facilitate to the non-linear estimation. Numerical results show that the VQC method can outperform modern compressed sensing techniques using an element-wise denoiser.

 

  • Related News & Events

    •  NEWS    Toshiaki Koike-Akino to give a seminar talk at EPFL on quantum AI
      Date: May 22, 2024
      MERL Contact: Toshiaki Koike-Akino
      Research Areas: Artificial Intelligence, Machine Learning
      Brief
      • Toshiaki Koike-Akino is invited to present a seminar talk at EPFL, Switzerland. The talk, entitled "Post-Deep Learning: Emerging Quantum AI Technology", will discuss the recent trends, challenges, and applications of quantum machine learning (QML) technologies. The seminar is organized by Prof. Volkan Cevher and Prof. Giovanni De Micheli. The event invites students, researchers, scholars and professors through EPFL departments including School of Engineering, Communication Science, Life Science, Machine Learning and AI Center.
    •  
    •  NEWS    MERL Researchers give a Tutorial Talk on Quantum Machine Learning for Sensing and Communications at IEEE VCC
      Date: November 28, 2023 - November 30, 2023
      Where: Virtual
      MERL Contacts: Toshiaki Koike-Akino; Pu (Perry) Wang
      Research Areas: Artificial Intelligence, Communications, Computational Sensing, Machine Learning, Signal Processing
      Brief
      • On November 28, 2023, MERL researchers Toshiaki Koike-Akino and Pu (Perry) Wang will give a 3-hour tutorial presentation at the first IEEE Virtual Conference on Communications (VCC). The talk, titled "Post-Deep Learning Era: Emerging Quantum Machine Learning for Sensing and Communications," addresses recent trends, challenges, and advances in sensing and communications. P. Wang presents use cases, industry trends, signal processing, and deep learning for Wi-Fi integrated sensing and communications (ISAC), while T. Koike-Akino discusses the future of deep learning, giving a comprehensive overview of artificial intelligence (AI) technologies, natural computing, emerging quantum AI, and their diverse applications. The tutorial is conducted virtually.

        IEEE VCC is a new fully virtual conference launched from the IEEE Communications Society, gathering researchers from academia and industry who are unable to travel but wish to present their recent scientific results and engage in conducive interactive discussions with fellow researchers working in their fields. It is designed to resolve potential hardship such as pandemic restrictions, visa issues, travel problems, or financial difficulties.
    •  
    •  NEWS    MERL Researchers gave a Tutorial Talk on Quantum Machine Learning for Sensing and Communications at IEEE GLOBECOM
      Date: December 8, 2022
      MERL Contacts: Toshiaki Koike-Akino; Pu (Perry) Wang
      Research Areas: Artificial Intelligence, Communications, Computational Sensing, Machine Learning, Signal Processing
      Brief
      • On December 8, 2022, MERL researchers Toshiaki Koike-Akino and Pu (Perry) Wang gave a 3.5-hour tutorial presentation at the IEEE Global Communications Conference (GLOBECOM). The talk, titled "Post-Deep Learning Era: Emerging Quantum Machine Learning for Sensing and Communications," addressed recent trends, challenges, and advances in sensing and communications. P. Wang presented on use cases, industry trends, signal processing, and deep learning for Wi-Fi integrated sensing and communications (ISAC), while T. Koike-Akino discussed the future of deep learning, giving a comprehensive overview of artificial intelligence (AI) technologies, natural computing, emerging quantum AI, and their diverse applications. The tutorial was conducted remotely. MERL's quantum AI technology was partly reported in the recent press release (https://us.mitsubishielectric.com/en/news/releases/global/2022/1202-a/index.html).

        The IEEE GLOBECOM is a highly anticipated event for researchers and industry professionals in the field of communications. Organized by the IEEE Communications Society, the flagship conference is known for its focus on driving innovation in all aspects of the field. Each year, over 3,000 scientific researchers submit proposals for program sessions at the annual conference. The theme of this year's conference was "Accelerating the Digital Transformation through Smart Communications," and featured a comprehensive technical program with 13 symposia, various tutorials and workshops.
    •  
    •  NEWS    MERL's Quantum Machine Learning Technology Featured in Mitsubishi Electric Corporation Press Release
      Date: December 2, 2022
      MERL Contacts: Toshiaki Koike-Akino; Kieran Parsons; Pu (Perry) Wang; Ye Wang
      Research Areas: Artificial Intelligence, Computational Sensing, Machine Learning, Signal Processing, Human-Computer Interaction
      Brief
      • Mitsubishi Electric Corporation announced its development of a quantum artificial intelligence (AI) technology that automatically optimizes inference models to downsize the scale of computation with quantum neural networks. The new quantum AI technology can be integrated with classical machine learning frameworks for diverse solutions.

        Mitsubishi Electric has confirmed that the technology can be incorporated in the world's first applications for terahertz (THz) imaging, Wi-Fi indoor monitoring, compressed sensing, and brain-computer interfaces. The technology is based on recent research by MERL's Connectivity & Information Processing team and Computational Sensing team.

        Mitsubishi Electric's new quantum machine learning (QML) technology realizes compact inference models by fully exploiting the enormous capacity of quantum computers to express exponentially larger-state space with the number of quantum bits (qubits). In a hybrid combination of both quantum and classical AI, the technology can compensate for limitations of classical AI to achieve superior performance while significantly downsizing the scale of AI models, even when using limited data.
    •  
    •  NEWS    MERL Scientists Presenting 5 Papers at IEEE International Conference on Communications (ICC) 2022
      Date: May 16, 2022 - May 20, 2022
      Where: Seoul, Korea
      MERL Contacts: Jianlin Guo; Toshiaki Koike-Akino; Philip V. Orlik; Kieran Parsons; Pu (Perry) Wang; Ye Wang
      Research Areas: Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Machine Learning, Signal Processing
      Brief
      • MERL Connectivity & Information Processing Team scientists remotely presented 5 papers at the IEEE International Conference on Communications (ICC) 2022, held in Seoul Korea on May 16-20, 2022. Topics presented include recent advancements in communications technologies, deep learning methods, and quantum machine learning (QML). Presentation videos are also found on our YouTube channel. In addition, K. J. Kim organized "Industrial Private 5G-and-beyond Wireless Networks Workshop" at the conference.

        IEEE ICC is one of two IEEE Communications Society’s flagship conferences (ICC and Globecom). Each year, close to 2,000 attendees from over 70 countries attend IEEE ICC to take advantage of a program which consists of exciting keynote session, robust technical paper sessions, innovative tutorials and workshops, and engaging industry sessions. This 5-day event is known for bringing together audiences from both industry and academia to learn about the latest research and innovations in communications and networking technology, share ideas and best practices, and collaborate on future projects.
    •  

  • Related Video

  • Related Research Highlights

  • Related Publication

  •  Liu, B., Koike-Akino, T., Wang, Y., Parsons, K., "Variational Quantum Compressed Sensing for Joint User and Channel State Acquisition in Grant-Free Device Access Systems", arXiv, May 2022.
    BibTeX arXiv
    • @article{Liu2022may2,
    • author = {Liu, Bryan and Koike-Akino, Toshiaki and Wang, Ye and Parsons, Kieran},
    • title = {Variational Quantum Compressed Sensing for Joint User and Channel State Acquisition in Grant-Free Device Access Systems},
    • journal = {arXiv},
    • year = 2022,
    • month = may,
    • url = {https://arxiv.org/abs/2205.08603}
    • }