LANTERN: Low-lAtency aNd privaTe Edge computing in Random-access Networks is an H2020-MSCA-IF project. It receives funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 101022113.


Paving the way to the future of the Internet of things

With the continuous rise of the Internet of things and the steady spread of connected devices, there is an increasing need concerning private edge computing and connectivity. This project will assist in fulfilling this need by researching low-latency and private edge computing networks and studying ways in which they could be developed in wireless random access networks. We aim to overcome the challenges of establishing foundations for privacy and reliability in latency-critical, multiserver and multiclient edge computing and in devising resilient coding schemes intertwined with energy-efficient scalable wireless random access methodologies.

Project objective

We are living in a world where connected devices outnumber human population, and this trend keeps growing: around 24.6 billion connections are forecasted in 2025—more than three times the estimated population. This gives rise to the Internet of Things (IoT) in which virtually all devices are interconnected and continuously share data. The IoT is a key enabler for a host of applications, such as intelligent transportation systems, smart cities, and smart grids. Thus it promises to transform the way we live. To realize the IoT, it is crucial and timely to develop a communication and computation infrastructure that is able to support the processing of a vast amount of time-sensitive data, for which a centralized computation is inadequate. Edge computing has emerged as a novel paradigm to guarantee very low-latency and high-bandwidth computing services. It involves moving the computation power from the cloud to where data is generated, by pooling the available resources at the network edge.

In this project, we investigate how low-latency and private edge computing protocols can be developed in wireless random-access networks. Relying on tools from information theory and coding theory, we will tackle the two following challenging objectives:

The results of this project will help paving the way to the full realization of the IoT in the near future.

Project description


Journal Papers

  1. Khac-Hoang Ngo, A. Lancho, G. Durisi, and A. Graell i Amat, “Unsourced multiple access with random user activity,” submitted to IEEE Trans. Inf. Theory, Jan. 2022. [arXiv] [Simulation code]

  2. G. Gur, C. de Alwis, Q.-V. Pham, Khac-Hoang Ngo, M. Liyanage, and P. Porambage, “A survey on integration of ICN and MEC for efficient B5G realization,” submitted to IEEE Open J. Commun. Soc., Jan 2022.

Conference papers

  1. Khac-Hoang Ngo, G. Durisi, and A. Graell i Amat, “Age of Information in Prioritized Random Access,” in 55rd Asilomar Conference on Signals, Systems, and Computers, CA, USA, Nov. 2021, invited paper. [arXiv] [Video] [Simulation code]

  2. Khac-Hoang Ngo, A. Lancho, G. Durisi, and A. Graell i Amat, “Massive uncoordinated access with random user activity,” in IEEE International Symposium on Information Theory (ISIT), 2021. [arXiv] [Video] [Simulation code]

  3. Khac-Hoang Ngo, N. T. Nguyen, T. Q. Dinh, T.-M. Hoang, and M. Juntti, “Low-latency and secure computation offloading assisted by hybrid relay-reflecting intelligent surface,” in International Conference on Advanced Technologies for Communications (ATC), Hanoi, Vietnam, Oct. 2021, Best Paper Award. [arXiv] [Video] [Simulation code]



  1. “Age of Information in Prioritized Random Access,” Communication System Group Seminar, Chalmers University of Technology, 21 Jan. 2022.

  2. “Massive Uncoordinated Random Access for the Internet of Things,” Advanced Institute of Engineering and Technology (AVITECH), University of Engineering and Technology, Vietnam National University-Hanoi, Vietnam, 11 May 2021.

  3. “Massive Uncoordinated Random Access,” Communication System Group Seminar, Chalmers University of Technology, 23 Apr. 2021.


All presentation videos related to LANTERN are available here.

Activities of the Fellow


  1. Ongoing traning for a Diploma in Teaching and Learning in Higher Education at Chalmers University of Technology
    Completed courses: Diversity and inclusion for learning in higher education (2 credits); University teaching and learning (2.5 credits); Theoretical perspectives on learning (2.5 credits); Supervising research students (3 credits); Supervising writing processes (2.5 credits)

  2. Attended workshop Mental health issues in academia and contemplative solutions organized by Alumnode, 9 Dec. 2021.

  3. Attended workshop series Navigate academia and maximize your potential organized by Chalmers Doctoral Students Guild and Dear Academia, 29 Oct – 3 Dec. 2021


  1. Chalmers University of Technology: Teaching Assistant
    • Fall 2021: Statistics and machine learning in high dimensions (master/PhD course, taught in English, 8 hours)
    • Spring 2021: Information theory (master/PhD course, taught in English, 16 hours)

Conference Organization

  1. Communication track chair, 2022 International Conference on Advanced Technologies For Communications (ATC), Hanoi, Vietnam, Oct. 2022.
  2. Special session chair, 25th International ITG Workshop on Smart Antennas (WSA), French Riviera, France, Nov. 2021.
  3. Special session chair, 2021 International Conference on Advanced Technologies For Communications (ATC), HCM City, Vietnam, Oct. 2021.


for various international journals and conferences.


  1. Administrator of telecom-vn – a Facebook group for Vietnamese researchers in telecommunications. Organize regular group seminars.
  2. Organize several online workshops on information and communication technologies for the Vietnamese community.

Reproduciple Research

The simulation codes of LANTERN are accessible at: The links are also associated to each paper in the list of publications.




My MSCA project LANTERN starts


I start my MSCA project LANTERN: Low-latency and private edge computing in random-access networks