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.

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  • Awards

    •  AWARD    MERL’s Paper on Wi-Fi Sensing Earns Top 3% Paper Recognition at ICASSP 2023, Selected as a Best Student Paper Award Finalist
      Date: June 9, 2023
      Awarded to: Cristian J. Vaca-Rubio, Pu Wang, Toshiaki Koike-Akino, Ye Wang, Petros Boufounos and Petar Popovski
      MERL Contacts: Petros T. Boufounos; Toshiaki Koike-Akino; Pu (Perry) Wang; Ye Wang
      Research Areas: Artificial Intelligence, Communications, Computational Sensing, Dynamical Systems, Machine Learning, Signal Processing
      Brief
      • A MERL Paper on Wi-Fi sensing was recognized as a Top 3% Paper among all 2709 accepted papers at the 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2023). Co-authored by Cristian Vaca-Rubio and Petar Popovski from Aalborg University, Denmark, and MERL researchers Pu Wang, Toshiaki Koike-Akino, Ye Wang, and Petros Boufounos, the paper "MmWave Wi-Fi Trajectory Estimation with Continous-Time Neural Dynamic Learning" was also a Best Student Paper Award finalist.

        Performed during Cristian’s stay at MERL first as a visiting Marie Skłodowska-Curie Fellow and then as a full-time intern in 2022, this work capitalizes on standards-compliant Wi-Fi signals to perform indoor localization and sensing. The paper uses a neural dynamic learning framework to address technical issues such as low sampling rate and irregular sampling intervals.

        ICASSP, a flagship conference of the IEEE Signal Processing Society (SPS), was hosted on the Greek island of Rhodes from June 04 to June 10, 2023. ICASSP 2023 marked the largest ICASSP in history, boasting over 4000 participants and 6128 submitted papers, out of which 2709 were accepted.
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    •  AWARD    Best Paper Award of 2022 IPSJ Transactions on Consumer Devices & Systems
      Date: March 27, 2023
      Awarded to: Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik, Hiroshi Mineno
      MERL Contacts: Jianlin Guo; Philip V. Orlik; Kieran Parsons
      Research Areas: Communications, Signal Processing
      Brief
      • MELCO/MERL research paper “IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1GHz Frequency Bands” has won the Best Paper Award of the 2022 IPSJ Transactions on Consumer Devices and Systems. The Information Processing Society of Japan (IPSJ) award was established in 1970 and is conferred on the authors of particularly excellent papers, which are published in the IPSJ journals and transactions. Our paper was published by the IPSJ Transaction on Consumer Device and System Vol. 29 in 2021 and authors are Yukimasa Nagai, Takenori Sumi, Jianlin Guo, Philip Orlik and Hiroshi Mineno.
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    •  AWARD    MERL receives 33rd ARIB Radio Achievement Award
      Date: June 28, 2022
      Awarded to: Yukimasa Nagai, Jianlin Guo, Shoichi Kitazawa, Kazuto Yano.
      MERL Contacts: Jianlin Guo; Philip V. Orlik
      Research Areas: Communications, Electric Systems
      Brief
      • Mitsubishi Electric Corporation (Yukimasa Nagai), MERL (Jianlin Guo), Muroran Institute of Technology (Shoichi Kitazawa) and Advanced Telecommunications Research Institute International (Kazuto Yano) jointly won the 33rd ARIB Radio Achievement Award with "IEEE 802.19.3 Standardization and Development for Sub-1 GHz Wireless Frequency Coexistence". The ARIB is an organization similar to the FCC in the U.S. It is responsible for setting standards for all radio communications in Japan at the request of the Ministry of Internal Affairs and Communications (MIC). In order to promote the effective use of radio waves, the "Radio Achievement Award" is given annually to an individual or organization that has made a special achievement in the effective use of radio waves. This award is the most prestigious award in the field of wireless communications in Japan.
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  • News & Events

    •  NEWS    MERL Researchers to Present 2 Conference and 11 Workshop Papers at NeurIPS 2024
      Date: December 10, 2024 - December 15, 2024
      Where: Advances in Neural Processing Systems (NeurIPS)
      MERL Contacts: Petros T. Boufounos; Matthew Brand; Ankush Chakrabarty; Anoop Cherian; François Germain; Toshiaki Koike-Akino; Christopher R. Laughman; Jonathan Le Roux; Jing Liu; Suhas Lohit; Tim K. Marks; Yoshiki Masuyama; Kieran Parsons; Kuan-Chuan Peng; Diego Romeres; Pu (Perry) Wang; Ye Wang; Gordon Wichern
      Research Areas: Artificial Intelligence, Communications, Computational Sensing, Computer Vision, Control, Data Analytics, Dynamical Systems, Machine Learning, Multi-Physical Modeling, Optimization, Robotics, Signal Processing, Speech & Audio, Human-Computer Interaction, Information Security
      Brief
      • MERL researchers will attend and present the following papers at the 2024 Advances in Neural Processing Systems (NeurIPS) Conference and Workshops.

        1. "RETR: Multi-View Radar Detection Transformer for Indoor Perception" by Ryoma Yataka (Mitsubishi Electric), Adriano Cardace (Bologna University), Perry Wang (Mitsubishi Electric Research Laboratories), Petros Boufounos (Mitsubishi Electric Research Laboratories), Ryuhei Takahashi (Mitsubishi Electric). Main Conference. https://neurips.cc/virtual/2024/poster/95530

        2. "Evaluating Large Vision-and-Language Models on Children's Mathematical Olympiads" by Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Joanna Matthiesen (Math Kangaroo USA), Kevin Smith (Massachusetts Institute of Technology), Josh Tenenbaum (Massachusetts Institute of Technology). Main Conference, Datasets and Benchmarks track. https://neurips.cc/virtual/2024/poster/97639

        3. "Probabilistic Forecasting for Building Energy Systems: Are Time-Series Foundation Models The Answer?" by Young-Jin Park (Massachusetts Institute of Technology), Jing Liu (Mitsubishi Electric Research Laboratories), François G Germain (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Gordon Wichern (Mitsubishi Electric Research Laboratories), Navid Azizan (Massachusetts Institute of Technology), Christopher R. Laughman (Mitsubishi Electric Research Laboratories), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories). Time Series in the Age of Large Models Workshop.

        4. "Forget to Flourish: Leveraging Model-Unlearning on Pretrained Language Models for Privacy Leakage" by Md Rafi Ur Rashid (Penn State University), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Shagufta Mehnaz (Penn State University), Ye Wang (Mitsubishi Electric Research Laboratories). Workshop on Red Teaming GenAI: What Can We Learn from Adversaries?

        5. "Spatially-Aware Losses for Enhanced Neural Acoustic Fields" by Christopher Ick (New York University), Gordon Wichern (Mitsubishi Electric Research Laboratories), Yoshiki Masuyama (Mitsubishi Electric Research Laboratories), François G Germain (Mitsubishi Electric Research Laboratories), Jonathan Le Roux (Mitsubishi Electric Research Laboratories). Audio Imagination Workshop.

        6. "FV-NeRV: Neural Compression for Free Viewpoint Videos" by Sorachi Kato (Osaka University), Takuya Fujihashi (Osaka University), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Takashi Watanabe (Osaka University). Machine Learning and Compression Workshop.

        7. "GPT Sonography: Hand Gesture Decoding from Forearm Ultrasound Images via VLM" by Keshav Bimbraw (Worcester Polytechnic Institute), Ye Wang (Mitsubishi Electric Research Laboratories), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories). AIM-FM: Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond Workshop.

        8. "Smoothed Embeddings for Robust Language Models" by Hase Ryo (Mitsubishi Electric), Md Rafi Ur Rashid (Penn State University), Ashley Lewis (Ohio State University), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Kieran Parsons (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories). Safe Generative AI Workshop.

        9. "Slaying the HyDRA: Parameter-Efficient Hyper Networks with Low-Displacement Rank Adaptation" by Xiangyu Chen (University of Kansas), Ye Wang (Mitsubishi Electric Research Laboratories), Matthew Brand (Mitsubishi Electric Research Laboratories), Pu Wang (Mitsubishi Electric Research Laboratories), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories). Workshop on Adaptive Foundation Models.

        10. "Preference-based Multi-Objective Bayesian Optimization with Gradients" by Joshua Hang Sai Ip (University of California Berkeley), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories), Ali Mesbah (University of California Berkeley), Diego Romeres (Mitsubishi Electric Research Laboratories). Workshop on Bayesian Decision-Making and Uncertainty. Lightning talk spotlight.

        11. "TR-BEACON: Shedding Light on Efficient Behavior Discovery in High-Dimensions with Trust-Region-based Bayesian Novelty Search" by Wei-Ting Tang (Ohio State University), Ankush Chakrabarty (Mitsubishi Electric Research Laboratories), Joel A. Paulson (Ohio State University). Workshop on Bayesian Decision-Making and Uncertainty.

        12. "MEL-PETs Joint-Context Attack for the NeurIPS 2024 LLM Privacy Challenge Red Team Track" by Ye Wang (Mitsubishi Electric Research Laboratories), Tsunato Nakai (Mitsubishi Electric), Jing Liu (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Kento Oonishi (Mitsubishi Electric), Takuya Higashi (Mitsubishi Electric). LLM Privacy Challenge. Special Award for Practical Attack.

        13. "MEL-PETs Defense for the NeurIPS 2024 LLM Privacy Challenge Blue Team Track" by Jing Liu (Mitsubishi Electric Research Laboratories), Ye Wang (Mitsubishi Electric Research Laboratories), Toshiaki Koike-Akino (Mitsubishi Electric Research Laboratories), Tsunato Nakai (Mitsubishi Electric), Kento Oonishi (Mitsubishi Electric), Takuya Higashi (Mitsubishi Electric). LLM Privacy Challenge. Won 3rd Place Award.

        MERL members also contributed to the organization of the Multimodal Algorithmic Reasoning (MAR) Workshop (https://marworkshop.github.io/neurips24/). Organizers: Anoop Cherian (Mitsubishi Electric Research Laboratories), Kuan-Chuan Peng (Mitsubishi Electric Research Laboratories), Suhas Lohit (Mitsubishi Electric Research Laboratories), Honglu Zhou (Salesforce Research), Kevin Smith (Massachusetts Institute of Technology), Tim K. Marks (Mitsubishi Electric Research Laboratories), Juan Carlos Niebles (Salesforce AI Research), Petar Veličković (Google DeepMind).
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    •  NEWS    Jianlin Guo delivered a keynote in IEEE ICC 2024 Workshop
      Date: June 13, 2024
      Where: IEEE International Conference on Communications (ICC)
      MERL Contacts: Jianlin Guo; Philip V. Orlik; Kieran Parsons; Pu (Perry) Wang
      Research Areas: Communications, Machine Learning, Signal Processing
      Brief
      • Jianlin Guo delivered a keynote titled "Private IoT Networks" in the IEEE International Conference on Communications (ICC) 2024 Workshop "Industrial Private 5G-and-Beyond Wireless Networks", held in Denver, Colorado from June 9-13. The ICC is one of two IEEE Communications Society’s flagship conferences.

        Abstract: With the advent of private 5G-and-Beyond communication technologies, private IoT networks have been emerging. In private IoT networks, network owners have full control on the network resource management. However, to fully realize private IoT networks, the upper layer technologies need to be developed as well. This keynote presents machine learning based anomaly detection in manufacturing systems, innovative multipath TCP technologies over heterogeneous wireless IoT networks, novel channel resource scheduling in private 5G networks and efficient wireless coexistence of the heterogeneous wireless systems.
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  • Research Highlights

  • Internships

    • CI0067: Internship - IoT Network Design methodology

      MERL is seeking a highly motivated and qualified intern to carry out research on mobile IoT network design methodology. The candidate is expected to develop innovative mobile network technologies to support UAV assisted IoT networks. The candidates should have knowledge of mobile network technologies such as path planning and cooperative network operations. Knowledge of UAV technology and mobility management is a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply. Start date for this internship is flexible and the duration is 3 months.

      The responsibilities of this intern position include (i) research on UAV assisted network design methodology; (ii) develop network configuration technologies to support UAV cooperative network operations; (iii) simulate and analyze the performance of developed technology.

    • CI0066: Internship - IoT Network Anomaly Detection

      MERL is seeking a highly motivated and qualified intern to conduct research on IoT network anomaly detection and analysis. The candidate is expected to develop innovative anomaly detection technologies that can proactively detect and analyze network failure in large-scale IOT networks. The candidate should have knowledge of LLM/ML and anomaly detection. Knowledge of network log analysis and network protocol a plus. Candidates in their junior or senior years of a Ph.D. program are encouraged to apply. Start date for this internship is flexible and the duration is 3 months.

      The responsibilities of this intern position include (i) research on anomaly detection in large-scale IoT networks; (ii) develop proactive network anomaly detection and analysis technologies; (iii) simulate and analyze the performance of developed technology.


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  • Recent Publications

    •  Nagai, Y., Guo, J., Rolfe, B.A., Sumi, T., Parsons, K., Orlik, P.V., "IEEE 802.19.3a Standardization: Updating Sub-1 GHz Band Wireless Coexistence Recommendations", IEEE Conference on Standards for Communications and Networking (CSCN), November 2024.
      BibTeX TR2024-161 PDF
      • @inproceedings{Nagai2024nov,
      • author = {Nagai, Yukimasa and Guo, Jianlin and Rolfe, Benjamin A. and Sumi, Takenori and Parsons, Kieran and Orlik, Philip V.}},
      • title = {IEEE 802.19.3a Standardization: Updating Sub-1 GHz Band Wireless Coexistence Recommendations},
      • booktitle = {IEEE Conference on Standards for Communications and Networking (CSCN)},
      • year = 2024,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2024-161}
      • }
    •  Sumi, T., Nagai, Y., Guo, J., Mineno, H., "Firmware Distribution with Erasure Code for IoT applications on IEEE 802.15.4g Mesh Network", Asia-Pacific Conference on Communications 2024, November 2024.
      BibTeX TR2024-153 PDF
      • @inproceedings{Sumi2024nov,
      • author = {Sumi, Takenori and Nagai, Yukimasa and Guo, Jianlin and Mineno, Hiroshi}},
      • title = {Firmware Distribution with Erasure Code for IoT applications on IEEE 802.15.4g Mesh Network},
      • booktitle = {Asia-Pacific Conference on Communications 2024},
      • year = 2024,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2024-153}
      • }
    •  Kojima, K., Koike-Akino, T., "Photonics × Machine Learning", FIOLS, September 2024.
      BibTeX TR2024-154 PDF
      • @inproceedings{Kojima2024sep,
      • author = {Kojima, Keisuke and Koike-Akino, Toshiaki}},
      • title = {Photonics × Machine Learning},
      • booktitle = {FIOLS},
      • year = 2024,
      • month = sep,
      • url = {https://www.merl.com/publications/TR2024-154}
      • }
    •  Rahman, M., Yataka, R., Kato, S., Wang, P., Li, P., Cardace, A., Boufounos, P.T., "MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception", European Conference on Computer Vision (ECCV), DOI: 10.1007/​978-3-031-72986-7_18, September 2024, pp. 306–322.
      BibTeX TR2024-117 PDF Data
      • @inproceedings{Rahman2024sep,
      • author = {Rahman, Mahbub and Yataka, Ryoma and Kato, Sorachi and Wang, Pu and Li, Peizhao and Cardace, Adriano and Boufounos, Petros T.}},
      • title = {MMVR: Millimeter-wave Multi-View Radar Dataset and Benchmark for Indoor Perception},
      • booktitle = {European Conference on Computer Vision (ECCV)},
      • year = 2024,
      • pages = {306–322},
      • month = sep,
      • publisher = {Springer},
      • doi = {10.1007/978-3-031-72986-7_18},
      • url = {https://www.merl.com/publications/TR2024-117}
      • }
    •  Kirihara, H., Ibuki, S., Fujihashi, T., Koike-Akino, T., Watanabe, T., "Point Cloud Geometry Compression using Parameterized Graph Fourier Transform", ACM SIGCOMM, DOI: 10.1145/​3672196.367340, August 2024, pp. 52-57.
      BibTeX TR2024-106 PDF
      • @inproceedings{Kirihara2024aug,
      • author = {Kirihara, Hinata and Ibuki, Shoichi and Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi}},
      • title = {Point Cloud Geometry Compression using Parameterized Graph Fourier Transform},
      • booktitle = {ACM SIGCOMM},
      • year = 2024,
      • pages = {52--57},
      • month = aug,
      • publisher = {ACM},
      • doi = {10.1145/3672196.367340},
      • url = {https://www.merl.com/publications/TR2024-106}
      • }
    •  Nagai, Y., Guo, J., Rolfe, B.A., Yano, K., Sumi, T., Parsons, K., Orlik, P.V., Wang, P., "Sub-1 GHz Band Wireless Coexistence Study for OFDM Systems in IEEE 802.19.3a", Workshop on Smart Radio for IoT Era (SRIoT), July 2024.
      BibTeX TR2024-090 PDF
      • @inproceedings{Nagai2024jul,
      • author = {Nagai, Yukimasa and Guo, Jianlin and Rolfe, Benjamin A. and Yano, Kazuto and Sumi, Takenori and Parsons, Kieran and Orlik, Philip V. and Wang, Pu}},
      • title = {Sub-1 GHz Band Wireless Coexistence Study for OFDM Systems in IEEE 802.19.3a},
      • booktitle = {Workshop on Smart Radio for IoT Era (SRIoT)},
      • year = 2024,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2024-090}
      • }
    •  Sun, Y., Guo, J., Parsons, K., Nagai, Y., "Improve Federated Learning Stability for Vehicle Trajectory Prediction", International Conference on Ubiquitous and Future Networks (UCIFN), July 2024.
      BibTeX TR2024-094 PDF
      • @inproceedings{Sun2024jul,
      • author = {Sun, Youbang and Guo, Jianlin and Parsons, Kieran and Nagai, Yukimasa}},
      • title = {Improve Federated Learning Stability for Vehicle Trajectory Prediction},
      • booktitle = {International Conference on Ubiquitous and Future Networks (UCIFN)},
      • year = 2024,
      • month = jul,
      • url = {https://www.merl.com/publications/TR2024-094}
      • }
    •  Fujihashi, T., Koike-Akino, T., Corcodel, R., "Graph-Based Analog Joint Source Channel Coding for 3D Haptic Communication", IEEE International Conference on Communications (ICC), DOI: 10.1109/​ICC51166.2024.10622893, June 2024.
      BibTeX TR2024-070 PDF
      • @inproceedings{Fujihashi2024jun,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Corcodel, Radu}},
      • title = {Graph-Based Analog Joint Source Channel Coding for 3D Haptic Communication},
      • booktitle = {IEEE International Conference on Communications (ICC)},
      • year = 2024,
      • month = jun,
      • publisher = {IEEE},
      • doi = {10.1109/ICC51166.2024.10622893},
      • issn = {1938-1883},
      • isbn = {978-1-7281-9054-9},
      • url = {https://www.merl.com/publications/TR2024-070}
      • }
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