MERL - Mitsubishi Electric Research Laboratories

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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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  • 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

    •  TALK   Prof. Pere Gilabert gave an invited talk at MERL on Machine Learning for Digital Predistortion Linearization of High Efficient Power Amplifier
      Date & Time: Tuesday, February 16, 2021; 11:00-12:00
      Speaker: Prof. Pere Gilabert, Universitat Politecnica de Catalunya, Barcelona, Spain
      MERL Host: Rui Ma
      Research Areas: Communications, Electronic and Photonic Devices, Machine Learning, Signal Processing
      Brief
      • Digital predistortion (DPD) linearization is the most common and spread solution to cope with power amplifiers (PA) inherent linearity versus efficiency trade-off. The use of new radio 5G spectrally efficient signals with high peak-to-average power ratios (PAPR) occupying wider bandwidths only aggravates such compromise. When considering wide bandwidth signals, carrier aggregation or multi-band configurations in high efficient transmitter architectures, such as Doherty PAs, load-modulated balanced amplifiers, envelope tracking PAs or outphasing transmitters, the number of parameters required in the DPD model to compensate for both nonlinearities and memory effects can be unacceptably high. This has a negative impact in the DPD model extraction/adaptation, because it increases the computational complexity and drives to over-fitting and uncertainty.
        This talk will discuss the use of machine learning techniques for DPD linearization. The use of artificial neural networks (ANNs) for adaptive DPD linearization and approaches to reduce the coefficients adaptation time will be discussed. In addition, an overview on several feature-extraction techniques used to reduce the number of parameters of the DPD linearization system as well as to ensure proper, well-conditioned estimation for related variables will be presented.
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    •  NEWS   MERL published four papers in 2020 IEEE Global Communications Conference
      Date: December 7, 2020 - December 11, 2020
      Where: Taipei, Taiwan
      MERL Contacts: Kyeong Jin (K.J.) Kim; Toshiaki Koike-Akino; Philip Orlik; Pu (Perry) Wang; Ye Wang
      Research Areas: Communications, Computational Sensing, Machine Learning, Signal Processing
      Brief
      • MERL researchers have published four papers in 2020 IEEE Global Communications Conference (GlobeComm). This conference is one of the two IEEE Communications Societies flagship conferences dedicated to Communications for Human and Machine Intelligence. Topics of the published papers include, transmit diversity schemes, coding for molecular networks, and location and human activity sensing via WiFi signals.
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  • Research Highlights

  • Internships

    • SP1537: Machine Learning for Wireless Communications

      MERL is seeking an intern to work on machine learning for wireless communication systems. The ideal candidate would be an experienced PhD student or post-graduate researcher working in wireless communications with a focus on machine learning methods. The candidate should have a detailed knowledge of wireless communications, with some experience in machine learning, MIMO, and/or channel equalization preferred. Strong programming skills in Python and machine learning frameworks are essential. The expected duration of the internship is 3-6 months with flexible start date and length. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • 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.

    • SP1512: Mutual Interference Mitigation

      The Signal Processing (SP) group at MERL is seeking a highly motivated intern to conduct fundamental research in mutual interference mitigation for automotive radar. Previous experience in waveform design, radar detection under interference, joint communication and sensing, interference mitigation, and deep learning for radar is highly preferred. Knowledge about automotive radar schemes (MIMO and waveform modulation, e.g., FMCW, PMCW, and OFDM) is a plus. The intern will collaborate with a small group of MERL researchers to develop novel algorithms, design experiments using MERL in-house testbed, and prepare results for patents and publication. Senior Ph.D. students with research focuses on signal processing, machine learning, optimization, applied mathematics, or related areas are encouraged to apply. The expected duration of the internship is 3 months with a flexible start date.


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  • Recent Publications

    •  Skvortcov, P., Phillips, I., Forysiak, W., Koike-Akino, T., Kojima, K., Parsons, K., Millar, D.S., "Huffman-Coded Sphere Shaping for Extended-Reach Single-Span Links", IEEE Journal of Selected Topics in Quantum Electronics, DOI: 10.1109/JSTQE.2021.3055476, Vol. 27, No. 3, February 2021.
      BibTeX TR2021-007 PDF
      • @article{Skvortcov2021feb,
      • author = {Skvortcov, Pavel and Phillips, Ian and Forysiak, Wladek and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran and Millar, David S.},
      • title = {Huffman-Coded Sphere Shaping for Extended-Reach Single-Span Links},
      • journal = {IEEE Journal of Selected Topics in Quantum Electronics},
      • year = 2021,
      • volume = 27,
      • number = 3,
      • month = feb,
      • doi = {10.1109/JSTQE.2021.3055476},
      • issn = {1558-4542},
      • url = {https://www.merl.com/publications/TR2021-007}
      • }
    •  Kojima, K., TaherSima, M., Koike-Akino, T., Jha, D., Tang, Y., Wang, Y., Parsons, K., "Deep Neural Networks for Inverse Design of Nanophotonic Devices", IEEE Journal of Lightwave Technology, DOI: 10.1109/JLT.2021.3050083, January 2021.
      BibTeX TR2021-001 PDF
      • @article{Kojima2021jan,
      • author = {Kojima, Keisuke and TaherSima, Mohammad and Koike-Akino, Toshiaki and Jha, Devesh and Tang, Yingheng and Wang, Ye and Parsons, Kieran},
      • title = {Deep Neural Networks for Inverse Design of Nanophotonic Devices},
      • journal = {IEEE Journal of Lightwave Technology},
      • year = 2021,
      • month = jan,
      • doi = {10.1109/JLT.2021.3050083},
      • issn = {1558-2213},
      • url = {https://www.merl.com/publications/TR2021-001}
      • }
    •  Kim, K.J., Liu, H., Lei, H., Ding, Z., Orlik, P.V., Poor, H.V., "A dCDD-Based Transmit Diversity Scheme for Downlink Pseudo-NOMA Systems", IEEE Transactions on Wireless Communications, DOI: 10.1109/TWC.2020.3031809, Vol. 20, No. 2, pp. 1217-1232, December 2020.
      BibTeX TR2020-176 PDF
      • @article{Kim2020dec2,
      • author = {Kim, Kyeong Jin and Liu, Hongwu and Lei, Hongjiang and Ding, Zhiguo and Orlik, Philip V. and Poor, H. Vincent},
      • title = {A dCDD-Based Transmit Diversity Scheme for Downlink Pseudo-NOMA Systems},
      • journal = {IEEE Transactions on Wireless Communications},
      • year = 2020,
      • volume = 20,
      • number = 2,
      • pages = {1217--1232},
      • month = dec,
      • doi = {10.1109/TWC.2020.3031809},
      • url = {https://www.merl.com/publications/TR2020-176}
      • }
    •  Matsumine, T., Koike-Akino, T., Wang, Y., "Polar Coding with Chemical Reaction Networks for Molecular Communications", IEEE Global Communications Conference (GLOBECOM), DOI: 10.1109/GLOBECOM42002.2020.9321980, December 2020.
      BibTeX TR2020-160 PDF Video
      • @inproceedings{Matsumine2020dec,
      • author = {Matsumine, Toshiki and Koike-Akino, Toshiaki and Wang, Ye},
      • title = {Polar Coding with Chemical Reaction Networks for Molecular Communications},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2020,
      • month = dec,
      • publisher = {IEEE},
      • doi = {10.1109/GLOBECOM42002.2020.9321980},
      • issn = {2576-6813},
      • isbn = {978-1-7281-8298-8},
      • url = {https://www.merl.com/publications/TR2020-160}
      • }
    •  Kim, K.J., Liu, H., Yeoh, P.L., Orlik, P.V., Poor, H.V., "Backhaul Reliability Analysis on Cluster-Based Transmit Diversity Schemes in Private Networks", IEEE Global Communications Conference (GLOBECOM), DOI: 10.1109/GLOBECOM42002.2020.9322178, December 2020.
      BibTeX TR2020-170 PDF
      • @inproceedings{Kim2020dec,
      • author = {Kim, Kyeong Jin and Liu, Hongwu and Yeoh, Phee Lep and Orlik, Philip V. and Poor, H. Vincent},
      • title = {Backhaul Reliability Analysis on Cluster-Based Transmit Diversity Schemes in Private Networks},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2020,
      • month = dec,
      • doi = {10.1109/GLOBECOM42002.2020.9322178},
      • url = {https://www.merl.com/publications/TR2020-170}
      • }
    •  Wang, P., Koike-Akino, T., Orlik, P.V., "Fingerprinting-Based Indoor Localization with Commercial MMWave WiFi: NLOS Propagation", IEEE Global Communications Conference (GLOBECOM), DOI: 10.1109/GLOBECOM42002.2020.9348144, December 2020.
      BibTeX TR2020-159 PDF
      • @inproceedings{Wang2020dec,
      • author = {Wang, Pu and Koike-Akino, Toshiaki and Orlik, Philip V.},
      • title = {Fingerprinting-Based Indoor Localization with Commercial MMWave WiFi: NLOS Propagation},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2020,
      • month = dec,
      • publisher = {IEEE},
      • doi = {10.1109/GLOBECOM42002.2020.9348144},
      • issn = {2576-6813},
      • isbn = {978-1-7281-8298-8},
      • url = {https://www.merl.com/publications/TR2020-159}
      • }
    •  Yu, J., Wang, P., Koike-Akino, T., Wang, Y., Orlik, P.V., "Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi", IEEE Global Communications Conference (GLOBECOM), December 2020.
      BibTeX TR2020-158 PDF
      • @inproceedings{Yu2020dec,
      • author = {Yu, Jianyuan and Wang, Pu and Koike-Akino, Toshiaki and Wang, Ye and Orlik, Philip V.},
      • title = {Human Pose and Seat Occupancy Classification with Commercial MMWave WiFi},
      • booktitle = {IEEE Global Communications Conference (GLOBECOM)},
      • year = 2020,
      • month = dec,
      • url = {https://www.merl.com/publications/TR2020-158}
      • }
    •  Teo, K.H., Chowdhury, N., Zhang, Y., Palacios, T., Yamanaka, K., Yamaguchi, Y., "Recent Development in 2D and 3D GaN devices for RF and Power Electronics Applications", IEEE International Symposium on Radio-Frequency Integration Technology (RFIT), November 2020.
      BibTeX TR2020-162 PDF
      • @inproceedings{Teo2020nov,
      • author = {Teo, Koon Hoo and Chowdhury, Nadim and Zhang, Yuhao and Palacios, Tomas and Yamanaka, Koji and Yamaguchi, Yutaro},
      • title = {Recent Development in 2D and 3D GaN devices for RF and Power Electronics Applications},
      • booktitle = {IEEE International Symposium on Radio-Frequency Integration Technology (RFIT)},
      • year = 2020,
      • month = nov,
      • url = {https://www.merl.com/publications/TR2020-162}
      • }
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