MERL - Mitsubishi Electric Research Laboratories

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Signal Processing

Acquisition and processing of information.

Our research in the area of signal processing encompasses a wide range of work in the areas of communications, sensing, estimation, localization, and speech and visual information processing. We explore novel approaches for signal acquisition and coding, methods to filter and recover signals in the presence of noise and other degrading factors, and techniques that infer meaning from the processed signals.

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  • Researchers

  • Awards

    •  AWARD   Excellent Presentation Award
      Date: January 25, 2021
      Awarded to: Takenori Sumi, Yukimasa Nagai, Jianlin Guo, Philip Orlik, Tatsuya Yokoyama, Hiroshi Mineno
      MERL Contacts: Jianlin Guo; Philip Orlik
      Research Areas: Communications, Machine Learning, Signal Processing
      Brief
      • MELCO and MERL researchers have won "Excellent Presentation Award" at the IPSJ/CDS30 (Information Processing Society of Japan/Consumer Devices and Systems 30th conferences) held on January 25, 2021. The paper titled "Sub-1 GHz Coexistence Using Reinforcement Learning Based IEEE 802.11ah RAW Scheduling" addresses coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. This paper proposes a novel method to allocate IEEE 802.11 RAW time slots using a Q-Learning technique. MERL and MELCO have been leading IEEE 802.19.3 coexistence standard development and this paper is a good candidate for future standard enhancement. The authors are Takenori Sumi, Yukimasa Nagai, Jianlin Guo, Philip Orlik, Tatsuya Yokoyama and Hiroshi Mineno.
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    •  AWARD   Outstanding Presentation Award at the 28th Conference of Information Processing Society of Japan/Consumer Device & Systems
      Date: October 20, 2020
      Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
      MERL Contacts: Jianlin Guo; Philip Orlik
      Research Areas: Communications, Optimization, Signal Processing
      Brief
      • MELCO and MERL researchers have won "Outstanding Presentation Award" at 28th Conference of Information Processing Society of Japan (IPSJ)/Consumer Device & Systems held on September 29-30, 2020. The paper titled "IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands" reports IEEE 802.19.3 standard development on coexistence between IEEE 802.11ah and IEEE 802.15.4g systems in the Sub-1 GHz frequency bands. MERL and MELCO have been leading this standard development and made major technical contributions, which propose methods to mitigate interference in smart meter systems. The authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
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    •  AWARD   Best Paper AWARD at International Workshop on Informatics (IWIN) 2020
      Date: September 11, 2020
      Awarded to: Yukimasa Nagai, Jianlin Guo, Takenori Sumi, Philip Orlik, Hiroshi Mineno
      MERL Contact: Jianlin Guo
      Research Areas: Communications, Signal Processing
      Brief
      • MELCO and MERL researchers have won one of two Best Paper Awards at International Workshop on Informatics (IWIN) 2020. The paper titled 'Hybrid CSMA/CA for Sub-1 GHz Frequency Band Coexistence of IEEE 802.11ah and IEEE 802.15.4g', reports research on the severity of interference between IEEE 802.11ah and IEEE 802.15.4g based networks and also proposes methods to mitigate this interference in smart meter systems. This research reported in this paper has also informed several of MELCO/MERL's contributions to the IEEE P802.19.3 task group which is developing standards to allow for improved coexistence in outdoor metering systems. Authors are Yukimasa Nagai, Jianlin Guo, Takenori Sumi, Philip Orlik and Hiroshi Mineno.
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  • News & Events

    •  NEWS   MERL Congratulates Recipients of 2022 IEEE Technical Field Awards in Signal Processing
      Date: July 26, 2021
      MERL Contacts: Petros Boufounos; Jonathan Le Roux; Philip Orlik; Anthony Vetro
      Research Areas: Signal Processing, Speech & Audio
      Brief
      • IEEE has announced that the recipients of the 2022 IEEE James L. Flanagan Speech and Audio Processing Award will be Hervé Bourlard (EPFL/Idiap Research Institute) and Nelson Morgan (ICSI), "For contributions to neural networks for statistical speech recognition," and the recipient of the 2022 IEEE Fourier Award for Signal Processing will be Ali Sayed (EPFL), "For contributions to the theory and practice of adaptive signal processing." More details about the contributions of Prof. Bourlard and Prof. Morgan can be found in the announcements by ICSI and EPFL, and those of Prof. Sayed in EPFL's announcement. Mitsubishi Electric Research Laboratories (MERL) has recently become the new sponsor of these two prestigious awards, and extends our warmest congratulations to all of the 2022 award recipients.

        The IEEE Board of Directors established the IEEE James L. Flanagan Speech and Audio Processing Award in 2002 for outstanding contributions to the advancement of speech and/or audio signal processing, while the IEEE Fourier Award for Signal Processing was established in 2012 for outstanding contribution to the advancement of signal processing, other than in the areas of speech and audio processing. Both awards have recognized the contributions of some of the most renowned pioneers and leaders in their respective fields. MERL is proud to support the recognition of outstanding contributions to the signal processing field through its sponsorship of these awards.
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    •  NEWS   MERL becomes new sponsor of two prestigious IEEE Technical Field Awards in Signal Processing
      Date: July 9, 2021
      MERL Contacts: Petros Boufounos; Jonathan Le Roux; Philip Orlik; Anthony Vetro
      Research Areas: Signal Processing, Speech & Audio
      Brief
      • Mitsubishi Electric Research Laboratories (MERL) has become the new sponsor of two prestigious IEEE Technical Field Awards in Signal Processing, the IEEE James L. Flanagan Speech and Audio Processing Award and the IEEE Fourier Award for Signal Processing, for the years 2022-2031. "MERL is proud to support the recognition of outstanding contributions to signal processing by sponsoring both the IEEE James L. Flanagan Speech and Audio Processing Award and the IEEE Fourier Award for Signal Processing. These awards celebrate the creativity and innovation in the field that touch many aspects of our lives and drive our society forward" said Dr. Anthony Vetro, VP and Director at MERL.

        The IEEE Board of Directors established the IEEE James L. Flanagan Speech and Audio Processing Award in 2002 for outstanding contributions to the advancement of speech and/or audio signal processing, while the IEEE Fourier Award for Signal Processing was established in 2012 for outstanding contribution to the advancement of signal processing, other than in the areas of speech and audio processing. Both awards have since recognized the contributions of some of the most renowned pioneers and leaders in their respective fields.

        By underwriting these IEEE Technical Field Awards, MERL continues to make a mark by supporting the advancement of technology that makes lasting changes in the world.
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  • Research Highlights

  • Internships

    • SP1517: AI-based spectrum management for 5G wireless networks and beyond

      MERL is seeking a highly motivated, qualified intern to join a thirteen weeks internship program. The ideal candidate will be expected to carry out research on emerging 5G wireless networks and beyond for industrial applications. The candidate is expected to develop innovative spectrum-based traffic recognition and optimal scheduling for local spectrum access. Candidates should have strong knowledge about 5G networks, spectrum management, cognitive radio, and neural network. Proficient programming skills with MATLAB, C++, Python (Pytorch), experience with ns-3 simulator, and strong mathematical analysis will be additional assets to this position. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • SP1543: Technologies for multimodal imaging

      MERL is seeking a motivated intern to assist in developing hardware and algorithms for multimodal imaging applications. The project involves integration of radar, camera, and depth sensors in a variety of sensing scenarios. The ideal candidate should have experience with hardware interfacing, C++, Python, and scripting methods. Experience with radar prototyping hardware is desired but not necessary. Good knowledge of computational imaging and/or radar imaging methods is a plus. This internship requires work that can only be done at MERL.

    • SP1542: Research in Computational Sensing

      The Computational Sensing team at MERL is seeking motivated and qualified individuals to assist in the development of computational methods for a variety of sensing applications. Ideal candidates should be Ph.D. students and have solid background and publication record in any of the following, or related areas: imaging inverse problems, learning for inverse problems, large-scale optimization, blind inverse scattering, radar/lidar/sonar imaging, sensing of dynamical systems, or wave-based inversion. Experience with experimentally measured data is desirable. Publication of the results produced during our internships is expected. The duration of the internships is anticipated to be 3-6 months. Start date is flexible. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.


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  • Recent Publications

    •  Wang, Y., Aeron, S., Rakin, A.S., Koike-Akino, T., Moulin, P., "Robust Machine Learning via Privacy/Rate-Distortion Theory", IEEE International Symposium on Information Theory (ISIT), July 2021.
      BibTeX TR2021-082 PDF Video Presentation
      • @inproceedings{Wang2021jul,
      • author = {Wang, Ye and Aeron, Shuchin and Rakin, Adnan S and Koike-Akino, Toshiaki and Moulin, Pierre},
      • title = {Robust Machine Learning via Privacy/Rate-Distortion Theory},
      • booktitle = {IEEE International Symposium on Information Theory (ISIT)},
      • year = 2021,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2021-082}
      • }
    •  Zeng, T., Guo, J., Kim, K.J., Parsons, K., Orlik, P.V., Di Cairano, S., Saad, W., "Multi-Task Federated Learning for Traffic Prediction and Its Application to Route Planning", IEEE Intelligent Vehicles Symposium, July 2021.
      BibTeX TR2021-083 PDF
      • @inproceedings{Zeng2021jul,
      • author = {Zeng, Tengchan and Guo, Jianlin and Kim, Kyeong Jin and Parsons, Kieran and Orlik, Philip V. and Di Cairano, Stefano and Saad, Walid},
      • title = {Multi-Task Federated Learning for Traffic Prediction and Its Application to Route Planning},
      • booktitle = {IEEE Intelligent Vehicles Symposium},
      • year = 2021,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2021-083}
      • }
    •  Koike-Akino, T., Wang, Y., "Protograph-Based Design for QC Polar Codes", IEEE International Symposium on Information Theory (ISIT), July 2021.
      BibTeX TR2021-080 PDF Video Presentation
      • @inproceedings{Koike-Akino2021jul,
      • author = {Koike-Akino, Toshiaki and Wang, Ye},
      • title = {Protograph-Based Design for QC Polar Codes},
      • booktitle = {IEEE International Symposium on Information Theory (ISIT)},
      • year = 2021,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2021-080}
      • }
    •  Fujihashi, T., Koike-Akino, T., Chen, S., Watanabe, T., "Wireless 3D Point Cloud Delivery Using Deep Graph Neural Networks", IEEE International Conference on Communications (ICC), June 2021.
      BibTeX TR2021-066 PDF
      • @inproceedings{Fujihashi2021jun,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Chen, Siheng and Watanabe, Takashi},
      • title = {Wireless 3D Point Cloud Delivery Using Deep Graph Neural Networks},
      • booktitle = {IEEE International Conference on Communications (ICC)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-066}
      • }
    •  Kim, K.J., Guo, J., Orlik, P.V., Nagai, Y., Poor, H.V., "A Cluster-Based Transmit Diversity Scheme for Asynchronous Joint Transmissions in Private Networks", IEEE International Conference on Communications (ICC), June 2021.
      BibTeX TR2021-075 PDF
      • @inproceedings{Kim2021jun,
      • author = {Kim, Kyeong Jin and Guo, Jianlin and Orlik, Philip V. and Nagai, Yukimasa and Poor, H. Vincent},
      • title = {A Cluster-Based Transmit Diversity Scheme for Asynchronous Joint Transmissions in Private Networks},
      • booktitle = {IEEE International Conference on Communications (ICC)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-075}
      • }
    •  Ma, Y., Boufounos, P.T., Mansour, H., Aeron, S., "Multiview Sensing with Unknown Permutations: An Optimal Transport Approach", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-047 PDF
      • @inproceedings{Ma2021jun,
      • author = {Ma, Yanting and Boufounos, Petros T. and Mansour, Hassan and Aeron, Shuchin},
      • title = {Multiview Sensing with Unknown Permutations: An Optimal Transport Approach},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-047}
      • }
    •  Chen, S., Eldar, Y., "Graph Signaling Denoising via Unrolling Networks", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-071 PDF
      • @inproceedings{Chen2021jun3,
      • author = {Chen, Siheng and Eldar, Yonina},
      • title = {Graph Signaling Denoising via Unrolling Networks},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-071}
      • }
    •  Chen, S., Eldar, Y., "Time-Varying Graph Signal Inpainting via Unrolling Networks", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-070 PDF
      • @inproceedings{Chen2021jun,
      • author = {Chen, Siheng and Eldar, Yonina},
      • title = {Time-Varying Graph Signal Inpainting via Unrolling Networks},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-070}
      • }
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