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.

  • 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 V. 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 V. 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

    •  TALK   Prof. Greg Ongie presents talk at MERL entitled Learning to Solve Inverse Problems in Computational Imaging: Recent Innovations
      Date & Time: Tuesday, October 12, 2021; 1:00 PM EST
      Speaker: Prof. Greg Ongie, Marquette University
      MERL Host: Hassan Mansour
      Research Areas: Computational Sensing, Machine Learning, Signal Processing
      Brief
      • Deep learning is emerging as powerful tool to solve challenging inverse problems in computational imaging, including basic image restoration tasks like denoising and deblurring, as well as image reconstruction problems in medical imaging. This talk will give an overview of the state-of-the-art supervised learning techniques in this area and discuss two recent innovations: deep equilibrium architectures, which allows one to train an effectively infinite-depth reconstruction network; and model adaptation methods, that allow one to adapt a pre-trained reconstruction network to changes in the imaging forward model at test time.
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    •  NEWS   MERL Researcher Kyeong Jin Kim organizes a workshop in 2022 IEEE International Conference on Communications (ICC).
      Date: May 16, 2022 - May 20, 2022
      Where: 2022 IEEE ICC
      MERL Contact: Kyeong Jin (K.J.) Kim
      Research Areas: Communications, Signal Processing
      Brief
      • Kyeong Jin Kim, a Senior Principal Research Scientist in the Signal Processing Group, organizes a workshop in 2022 IEEE International Conference on Communications (ICC). The workshop is titled, "Industrial Private 5G-and-beyond Wireless Networks," and aims to bring researchers for technical discussion on fundamental and practically relevant questions to many emerging challenges in industrial private wireless networks. This workshop is also being organized with the help of other researchers from Huawei Technology, Princeton University, Aalborg University, Jinan University, and South China University of Technology. IEEE ICC is one of two IEEE Communications Society's flagship conferences.
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  • Research Highlights

  • Internships

    • 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.

    • 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.

    • MD1696: Advanced RF Technologies

      Mitsubishi Electric Research Laboratories (Cambridge, MA) is seeking a highly motivated, qualified individual to join our 3 month internship program of research on advanced RF technologies. The ideal candidate should be a senior Ph.D. student with good experience in microwave power amplifier/RF active circuit design and experiment, RF front end systems. Familiarity with ADS and Matlab is required. Knowledge of radio system architecture and FPGA (signal processing) would be an asset. 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, P., Koike-Akino, T., Ma, R., Orlik, P.V., Yamashita, G., Tsujita, W., Nakajima, M., "Learning-Based THz Multi-Layer Imaging for High-Capacity Positioning", International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz), November 2021.
      BibTeX TR2021-098 PDF
      • @inproceedings{Wang2021nov,
      • author = {Wang, Perry and Koike-Akino, Toshiaki and Ma, Rui and Orlik, Philip V. and Yamashita, Genki and Tsujita, Wataru and Nakajima, M.},
      • title = {Learning-Based THz Multi-Layer Imaging for High-Capacity Positioning},
      • booktitle = {International Conference on Infrared, Millimeter, and Terahertz Waves (IRMMW-THz)},
      • year = 2021,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2021-098}
      • }
    •  Rakin, A.S., Wang, Y., Aeron, S., Koike-Akino, T., Moulin, P., Parsons, K., "Towards Universal Adversarial Examples and Defenses", IEEE Information Theory Workshop, October 2021.
      BibTeX TR2021-125 PDF Video
      • @inproceedings{Rakin2021oct,
      • author = {Rakin, Adnan S and Wang, Ye and Aeron, Shuchin and Koike-Akino, Toshiaki and Moulin, Pierre and Parsons, Kieran},
      • title = {Towards Universal Adversarial Examples and Defenses},
      • booktitle = {IEEE Information Theory Workshop},
      • year = 2021,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2021-125}
      • }
    •  Jurdi, R., Guo, J., Kim, K.J., Orlik, P.V., Nagai, Y., "Queueing Delay Analysis of Mixed Traffic in Time Sensitive Networks", International Conference on Intelligent Manufacturing and Automation Engineering (ICIMA), October 2021.
      BibTeX TR2021-122 PDF
      • @inproceedings{Jurdi2021oct,
      • author = {Jurdi, Rebal and Guo, Jianlin and Kim, Kyeong Jin and Orlik, Philip V. and Nagai, Yukimasa},
      • title = {Queueing Delay Analysis of Mixed Traffic in Time Sensitive Networks},
      • booktitle = {International Conference on Intelligent Manufacturing and Automation Engineering (ICIMA)},
      • year = 2021,
      • month = oct,
      • url = {https://www.merl.com/publications/TR2021-122}
      • }
    •  Kojima, K., Koike-Akino, T., Tang, Y., Wang, Y., "Inverse design for integrated photonics using deep neural network" in Integrated Nanophotonics (Wiley-VCH book chapter), September 2021.
      BibTeX TR2021-119 PDF
      • @incollection{Kojima2021sep,
      • author = {Kojima, Keisuke and Koike-Akino, Toshiaki and Tang, Yingheng and Wang, Ye},
      • title = {Inverse design for integrated photonics using deep neural network},
      • booktitle = {Integrated Nanophotonics (Wiley-VCH book chapter)},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-119}
      • }
    •  Koike-Akino, T., Wang, Y., Kojima, K., Parsons, K., Yoshida, T., "Zero-Multiplier Sparse DNN Equalization for Fiber-Optic QAM Systems with Probabilistic Amplitude Shaping", European Conference on Optical Communication (ECOC), September 2021.
      BibTeX TR2021-110 PDF
      • @inproceedings{Koike-Akino2021sep,
      • author = {Koike-Akino, Toshiaki and Wang, Ye and Kojima, Keisuke and Parsons, Kieran and Yoshida, Tsuyoshi},
      • title = {Zero-Multiplier Sparse DNN Equalization for Fiber-Optic QAM Systems with Probabilistic Amplitude Shaping},
      • booktitle = {European Conference on Optical Communication (ECOC)},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-110}
      • }
    •  Skvortcov, P., Koike-Akino, T., Millar, D.S., Kojima, K., Parsons, K., "Dual Coding Concatenation for Burst-Error Correction in Probabilistic Amplitude Shapin", European Conference on Optical Communication (ECOC), September 2021.
      BibTeX TR2021-111 PDF
      • @inproceedings{Skvortcov2021sep2,
      • author = {Skvortcov, Pavel and Koike-Akino, Toshiaki and Millar, David S. and Kojima, Keisuke and Parsons, Kieran},
      • title = {Dual Coding Concatenation for Burst-Error Correction in Probabilistic Amplitude Shapin},
      • booktitle = {European Conference on Optical Communication (ECOC)},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-111}
      • }
    •  Skvortcov, P., Millar, D.S., Phillips, I., Forysiak, W., Koike-Akino, T., Kojima, K., Parsons, K., "Experimental Analysis of Mismatched Soft-Demapping for Probabilistic Shaping in Short-Reach Nonlinear Transmission", European Conference on Optical Communication (ECOC), September 2021.
      BibTeX TR2021-109 PDF
      • @inproceedings{Skvortcov2021sep,
      • author = {Skvortcov, Pavel and Millar, David S. and Phillips, Ian and Forysiak, Wladek and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran},
      • title = {Experimental Analysis of Mismatched Soft-Demapping for Probabilistic Shaping in Short-Reach Nonlinear Transmission},
      • booktitle = {European Conference on Optical Communication (ECOC)},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-109}
      • }
    •  Liu, B., Guo, J., Koike-Akino, T., Wang, Y., Kim, K.J., Parsons, K., Orlik, P.V., Hashimoto, S., Yuan, J., "Anomaly Detection and Diagnosis Using Pre-Processing and Time-Delay Autoencoder", IEEE International conference on emerging technologies and factory automation, September 2021.
      BibTeX TR2021-107 PDF
      • @inproceedings{Liu2021sep,
      • author = {Liu, Bryan and Guo, Jianlin and Koike-Akino, Toshiaki and Wang, Ye and Kim, Kyeong Jin and Parsons, Kieran and Orlik, Philip V. and Hashimoto, Shigeru and Yuan, Jinhong},
      • title = {Anomaly Detection and Diagnosis Using Pre-Processing and Time-Delay Autoencoder},
      • booktitle = {IEEE International conference on emerging technologies and factory automation},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-107}
      • }
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