Communications

Wireless and optical communications.

We conduct advanced research in wireless and optical communications from the network layer down to the physical layer, including highly reliable machine-to-machine wireless networks, routing and scheduling for IoT networks, massive MIMO for 5G systems, flexible wideband RF front-end architectures, advanced error correction coding, and novel modulation and transmission techniques with adaptive signal processing for coherent fiber-optic and free-space optical communications.

  • Researchers

  • Awards

    •  AWARD   Toshiaki Koike-Akino elected Fellow of Optica
      Date: November 18, 2021
      Awarded to: Toshiaki Koike-Akino
      MERL Contact: Toshiaki Koike-Akino
      Research Areas: Communications, Electronic and Photonic Devices, Signal Processing
      Brief
      • Toshiaki Koike-Akino's research activities in communications, error control coding and optical technologies at MERL have earned him election as a Fellow Member of Optica (formerly OSA), the foremost professional association in optics and photonics worldwide. Fellow membership in Optica is limited to no more than ten percent of the membership and is reserved for members who have served with distinction in the advancement of optics and photonics. Koike-Akino is one of 106 members from 24 countries in Optica’s 2022 Fellows Class, elected during the Board of Directors of Optica meeting held on 2nd of November, 2021.

        “Congratulations to the 2022 Optica Fellows,” said 2021 President Connie Chang-Hasnain, University of California, Berkeley, USA. “These members exemplify what it means to be a leader in optics and photonics. Your election, by your peers, confirms the important contributions made within our field. Thank you for your dedication to Optica, and for advancing the science of light.”

        Koike-Akino's elevation to Fellow is specifically “for outstanding and innovative contributions to R&D in enabling technologies for optical communications, including nonlinear equalizers, high-dimensional modulations, and FEC (Forward Error Correction),” said Meredith Smith, Director, Optica Awards and Honors Office. "Again, congratulations on joining this esteemed group of Optica members."

        About Optica

        Optica (formerly OSA) is dedicated to promoting the generation, application, archiving and dissemination of knowledge in optics and photonics worldwide. Founded in 1916, it is the leading organization for scientists, engineers, business professionals, students and others interested in the science of light. Optica’s renowned publications, meetings, online resources and in-person activities fuel discoveries, shape real-life applications and accelerate scientific, technical and educational achievement.
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    •  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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  • News & Events

    •  EVENT   Prof. Melanie Zeilinger of ETH to give keynote at MERL's Virtual Open House
      Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
      Speaker: Prof. Melanie Zeilinger, ETH
      Location: Virtual Event
      Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
      Brief
      • MERL is excited to announce the second keynote speaker for our Virtual Open House 2021:
        Prof. Melanie Zeilinger from ETH .

        Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

        Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Zeilinger's talk is scheduled for 3:15pm - 3:45pm (EST).

        Registration: https://mailchi.mp/merl/merlvoh2021

        Keynote Title: Control Meets Learning - On Performance, Safety and User Interaction

        Abstract: With increasing sensing and communication capabilities, physical systems today are becoming one of the largest generators of data, making learning a central component of autonomous control systems. While this paradigm shift offers tremendous opportunities to address new levels of system complexity, variability and user interaction, it also raises fundamental questions of learning in a closed-loop dynamical control system. In this talk, I will present some of our recent results showing how even safety-critical systems can leverage the potential of data. I will first briefly present concepts for using learning for automatic controller design and for a new safety framework that can equip any learning-based controller with safety guarantees. The second part will then discuss how expert and user information can be utilized to optimize system performance, where I will particularly highlight an approach developed together with MERL for personalizing the motion planning in autonomous driving to the individual driving style of a passenger.
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    •  EVENT   Prof. Ashok Veeraraghavan of Rice University to give keynote at MERL's Virtual Open House
      Date & Time: Thursday, December 9, 2021; 1:00pm - 5:30pm EST
      Speaker: Prof. Ashok Veeraraghavan, Rice University
      Location: Virtual Event
      Research Areas: Applied Physics, Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Electric Systems, Electronic and Photonic Devices, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Digital Video, Human-Computer Interaction, Information Security
      Brief
      • MERL is excited to announce the first keynote speaker for our Virtual Open House 2021:
        Prof. Ashok Veeraraghavan from Rice University.

        Our virtual open house will take place on December 9, 2021, 1:00pm - 5:30pm (EST).

        Join us to learn more about who we are, what we do, and discuss our internship and employment opportunities. Prof. Veeraraghavan's talk is scheduled for 1:15pm - 1:45pm (EST).

        Registration: https://mailchi.mp/merl/merlvoh2021

        Keynote Title: Computational Imaging: Beyond the limits imposed by lenses.

        Abstract: The lens has long been a central element of cameras, since its early use in the mid-nineteenth century by Niepce, Talbot, and Daguerre. The role of the lens, from the Daguerrotype to modern digital cameras, is to refract light to achieve a one-to-one mapping between a point in the scene and a point on the sensor. This effect enables the sensor to compute a particular two-dimensional (2D) integral of the incident 4D light-field. We propose a radical departure from this practice and the many limitations it imposes. In the talk we focus on two inter-related research projects that attempt to go beyond lens-based imaging.

        First, we discuss our lab’s recent efforts to build flat, extremely thin imaging devices by replacing the lens in a conventional camera with an amplitude mask and computational reconstruction algorithms. These lensless cameras, called FlatCams can be less than a millimeter in thickness and enable applications where size, weight, thickness or cost are the driving factors. Second, we discuss high-resolution, long-distance imaging using Fourier Ptychography, where the need for a large aperture aberration corrected lens is replaced by a camera array and associated phase retrieval algorithms resulting again in order of magnitude reductions in size, weight and cost. Finally, I will spend a few minutes discussing how the wholistic computational imaging approach can be used to create ultra-high-resolution wavefront sensors.
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  • Research Highlights

  • Internships

    • SP1733: ML for GNSS-based Applications

      MERL is seeking a highly motivated, qualified intern to work on machine learning for Global Navigation Satellite System (GNSS) applications. The ideal candidate is working towards a PhD and is expected to develop innovative machine learning technologies to increase accuracy and integrity of GNSS-based positioning systems. Candidates should have strong knowledge about as many as possible of GNSS signal processing for multipath mitigation, handling RINEX data, neural network and learning techniques, such as feature extraction, deep machine learning, reinforcement learning, domain adaptation, and distributed learning. Proficient programming skills with PyTorch, Matlab, and C++, 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.

    • SP1711: Advanced Network Design

      MERL is seeking a highly motivated and qualified intern to join the Signal Processing Group for a three month internship program. The ideal candidate will be expected to carry out research on network design and optimization methods including AI assisted networking. The candidate is expected to develop innovative network configuration technologies to support emerging IoT applications. The candidates should have knowledge of network technologies such as network slicing, software defined networking and/or semantic networking. Knowledge of the communication technologies such as 3GPP-5G or IEEE 802 WLAN/WPAN standards is a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.

    • SP1710: Distributed Learning and Computing over Networks

      MERL is seeking a highly motivated and qualified intern to join the Signal Processing Group for a three month internship program. The ideal candidate will be expected to carry out research on collaborative learning between infrastructure, devices, and vehicles. The candidate is expected to develop distributed learning for various applications, including autonomous driving, smart infrastructure, mobile networks, etc.. The candidate should have knowledge of federated learning and distributed computing, networking and over-the-air-computation. Knowledge of scheduling, spectrum management, and mathematical analysis for convergence testing is a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply.


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  • Recent Publications

    •  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}
      • }
    •  Matsumine, T., Koike-Akino, T., Ochiai, H., "A Low-Complexity Probabilistic Amplitude Shaping with Short Linear Block Codes", IEEE Transactions on Communications, September 2021.
      BibTeX TR2021-117 PDF
      • @article{Matsumine2021sep,
      • author = {Matsumine, Toshiki and Koike-Akino, Toshiaki and Ochiai, Hideki},
      • title = {A Low-Complexity Probabilistic Amplitude Shaping with Short Linear Block Codes},
      • journal = {IEEE Transactions on Communications},
      • year = 2021,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2021-117}
      • }
    •  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), DOI: 10.1109/​ECOC52684.2021.9605870, September 2021.
      BibTeX TR2021-110 PDF Presentation
      • @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,
      • publisher = {IEEE},
      • doi = {10.1109/ECOC52684.2021.9605870},
      • isbn = {978-1-6654-3868-1},
      • 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 Shaping", European Conference on Optical Communication (ECOC), DOI: 10.1109/​ECOC52684.2021.9605842, September 2021.
      BibTeX TR2021-111 PDF Presentation
      • @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 Shaping},
      • booktitle = {European Conference on Optical Communication (ECOC)},
      • year = 2021,
      • month = sep,
      • publisher = {IEEE},
      • doi = {10.1109/ECOC52684.2021.9605842},
      • isbn = {978-1-6654-3868-1},
      • 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), DOI: 10.1109/​ECOC52684.2021.9605820, 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,
      • publisher = {IEEE},
      • doi = {10.1109/ECOC52684.2021.9605820},
      • isbn = {978-1-6654-3868-1},
      • 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}
      • }
    •  Koike-Akino, T., Wang, Y., "Evolution of Polar Coding", IEEE International Symposium on Topics in Coding (ISTC), August 2021.
      BibTeX TR2021-104 PDF
      • @inproceedings{Koike-Akino2021aug,
      • author = {Koike-Akino, Toshiaki and Wang, Ye},
      • title = {Evolution of Polar Coding},
      • booktitle = {IEEE International Symposium on Topics in Coding (ISTC)},
      • year = 2021,
      • month = aug,
      • url = {https://www.merl.com/publications/TR2021-104}
      • }
    •  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 Video
      • @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}
      • }
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