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 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.
    •  
    •  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.
    •  
    •  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.
    •  

    See All Awards for Signal Processing
  • News & Events

    •  NEWS   Karl Berntorp gave an invited lecture at University of Houston
      Date: April 22, 2021
      Where: Houston, Texas
      MERL Contact: Karl Berntorp
      Research Areas: Control, Dynamical Systems, Robotics, Signal Processing
      Brief
      • The invited seminar "System Design, Planning, and Control for Autonomous Driving" was part of the Distinguished Seminar series at the Department of Mechanical Engineering at the University of Houston, Houston, Tx. The invited lecture described MERL research related to the different system components involved in autonomous driving, with particular focus on motion-planning and predictive-control methods.
    •  
    •  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.
    •  

    See All News & Events for Signal Processing
  • Research Highlights

  • Internships

    • SP1475: Advanced Signal Processing for Metasurface

      MERL is seeking a highly motivated, qualified intern to join an internship program. The ideal candidate will be expected to carry out research on Advanced Signal Processing for Metasurface. The candidate is expected to develop innovative signal processing for metasurface aided various applications. Candidates should have strong knowledge about electromagnetic field analysis for metasurface, passive beamforming, interference mitigation, and channel estimation. Proficient programming skills with Python, 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. The expected duration of the internship is 3-6 months, with a flexible start date in 2020. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • CA1519: Estimation for High-Precision Positioning

      MERL is seeking a highly motivated candidate for development of next-generation high-precision positioning methods for autonomous systems applications, e.g., autonomous driving. The candidate will work with the Control for Autonomy team and the Signal Processing group in developing satellite-based positioning methods using information from multiple sources. Previous experience with at least some of the Bayesian inference, distributed estimation, satellite navigation systems, is highly desirable. Solid knowledge in MATLAB is required, working experience in C/C++ is desired, and previous experience with satellite navigation packages such as RTKLib is a merit. PhD candidates meeting the above requirements are encouraged to apply. The expected duration of the internship is 3-6 months with flexible start date. This internship is preferred to be onsite at MERL, but may be done remotely where you live if the COVID pandemic makes it necessary.

    • SP1307: Vehicular traffic environment sensing

      MERL is seeking a highly motivated, qualified intern to join a three month internship program. The ideal candidate will be expected to carry out research on environmental sensing in high frequency bands. The candidate is expected to develop innovative sensing technologies. Candidates should have strong knowledge about neural network and learning techniques, such as machine learning, deep learning, shallow learning, and distributed learning. In addition, understanding of spectrum sensing and wireless communications technologies is necessary. Proficient programming skills with Python, 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.


    See All Internships for Signal Processing
  • Recent Publications

    •  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}
      • }
    •  Hyder, R., Mansour, H., Ma, Y., Boufounos, P.T., Wang, P., "A Consensus Equilibrium Solution for Deep Image Prior Powered by Red", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-046 PDF
      • @inproceedings{Hyder2021jun,
      • author = {Hyder, Rakib and Mansour, Hassan and Ma, Yanting and Boufounos, Petros T. and Wang, Perry},
      • title = {A Consensus Equilibrium Solution for Deep Image Prior Powered by Red},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-046}
      • }
    •  Yao, G., Wang, P., Berntorp, K., Mansour, H., Boufounos, P.T., Orlik, P.V., "Extended Object Tracking with Automotive Radar Using B-Spline Chained Ellipses Model", IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2021.
      BibTeX TR2021-048 PDF
      • @inproceedings{Yao2021jun,
      • author = {Yao, Gang and Wang, Perry and Berntorp, Karl and Mansour, Hassan and Boufounos, Petros T. and Orlik, Philip V.},
      • title = {Extended Object Tracking with Automotive Radar Using B-Spline Chained Ellipses Model},
      • booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
      • year = 2021,
      • month = jun,
      • url = {https://www.merl.com/publications/TR2021-048}
      • }
    •  Tang, Y., Kojima, K., Koike-Akino, T., Wang, Y., Jha, D., Parsons, K., Qi, M., "Nano-Optic Broadband Power Splitter Design via Cycle-Consistent Adversarial Deep Learning", Conference on Lasers and Electro-Optics (CLEO), May 2021.
      BibTeX TR2021-045 PDF Presentation
      • @inproceedings{Tang2021may3,
      • author = {Tang, Yingheng and Kojima, Keisuke and Koike-Akino, Toshiaki and Wang, Ye and Jha, Devesh and Parsons, Kieran and Qi, Minghao},
      • title = {Nano-Optic Broadband Power Splitter Design via Cycle-Consistent Adversarial Deep Learning},
      • booktitle = {Conference on Lasers and Electro-Optics (CLEO)},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-045}
      • }
    •  Fujihashi, T., Koike-Akino, T., Watanabe, T., Orlik, P.V., "HoloCast+: Hybrid Digital-Analog Transmission for Graceful Point Cloud Delivery with Graph Fourier Transform", IEEE Transactions on Multimedia, DOI: 10.1109/​TMM.2021.3077772, May 2021.
      BibTeX TR2021-043 PDF
      • @article{Fujihashi2021may,
      • author = {Fujihashi, Takuya and Koike-Akino, Toshiaki and Watanabe, Takashi and Orlik, Philip V.},
      • title = {HoloCast+: Hybrid Digital-Analog Transmission for Graceful Point Cloud Delivery with Graph Fourier Transform},
      • journal = {IEEE Transactions on Multimedia},
      • year = 2021,
      • month = may,
      • doi = {10.1109/TMM.2021.3077772},
      • url = {https://www.merl.com/publications/TR2021-043}
      • }
    •  Pan, C., Chen, S., Ortega, A., "Spatio-Temporal Graph Scattering Transform", International Conference on Learning Representations (ICLR), May 2021.
      BibTeX TR2021-044 PDF
      • @inproceedings{Pan2021may,
      • author = {Pan, Chao and Chen, Siheng and Ortega, Antonio},
      • title = {Spatio-Temporal Graph Scattering Transform},
      • booktitle = {International Conference on Learning Representations (ICLR)},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-044}
      • }
    •  Nagai, Y., Sumi, T., Guo, J., Orlik, P.V., Mineno, H., "IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands", Information Processing Society of Japan/Consumer Device and System Transaction, Vol. 11, No. 5, May 2021.
      BibTeX TR2021-035 PDF
      • @article{Nagai2021may,
      • author = {Nagai, Yukimasa and Sumi, Takenori and Guo, Jianlin and Orlik, Philip V. and Mineno, Hiroshi},
      • title = {IEEE 802.19.3 Standardization for Coexistence of IEEE 802.11ah and IEEE 802.15.4g Systems in Sub-1 GHz Frequency Bands},
      • journal = {Information Processing Society of Japan/Consumer Device and System Transaction},
      • year = 2021,
      • volume = 11,
      • number = 5,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-035}
      • }
    •  Tang, Y., Kojima, K., Gotoda, M., Nishikawa, S., Hayashi, S., Koike-Akino, T., Parsons, K., Meissner, T., Song, B., Sang, F., Yi, X., Klamkin, J., "InP Grating Coupler Design for Vertical Coupling of InP and Silicon Chips," Tech. Rep. TR2021-034, MERL Technical Report, May 2021.
      BibTeX TR2021-034 PDF
      • @techreport{Tang2021may2,
      • author = {Tang, Yingheng and Kojima, Keisuke and Gotoda, Mitsunobu and Nishikawa, Satoshi and Hayashi, Shusaku and Koike-Akino, Toshiaki and Parsons, Kieran and Meissner, Thomas and Song, Bowen and Sang, Fengqiao and Yi, Xiongsheng and Klamkin, Jonathan},
      • title = {InP Grating Coupler Design for Vertical Coupling of InP and Silicon Chips},
      • institution = {MERL Technical Report},
      • year = 2021,
      • month = may,
      • url = {https://www.merl.com/publications/TR2021-034}
      • }
    See All Publications for Signal Processing
  • Videos

  • Software Downloads