Ahmed Abdelgawwad

Ahmed2017 (002)

PhD Research Fellow
Mobile Communications Group
Department of ICT
Faculty of Engineering and Science
University of Agder

4898 Grimstad
Jon Lilletunsvei 9
Office C5 138
Phone: +47 3723 3263
ahmed.abdel-gawwad(at)uia.no

Ahmed Abdelgawwad was born in Minya, Egypt in 1991. In 2013 and 2015 he received the bachelor and the master’s degree with honours in network engineering from the German University in Cairo (GUC). His master’s degree was related to complexity reduction of 3D ray-tracing for indoor coverage solutions.

Since December 2016, he is working towards his PhD degree under the supervision of Professor Matthias Pätzold.

His research interests and background includes network modelling and simulation, channel modelling for fall detection systems, non-stationary channel models, and time-frequency analysis for non-stationary channel models.

Publications

Conferences

  1. R. Hicheri, A. Abdelgawwad, M. Pätzold:
    A new non-stationary 3D channel model with time-variant path gains for indoor human activity recognition,
    in: Innovative and Intelligent Technology-Based Services for Smart Environments, CRC Press, 2021, pp. 68-74.
  2. A. Abdelgawwad, A. Catala, M. Pätzold:
    Doppler power characteristics obtained from calibrated channel state information for human activity recognition,
    in Proc. 91st Veh. Technol. Conference, VTC 2020-Spring. Antwerp, Belgium, May 2020, DOI 10.1109/VTC2020-Spring48590.2020.9129187.
  3. M. Muaaz, A. Abdelgawwad, and M. Pätzold:
    The influence of human walking activities on the Doppler characteristics of non-stationary indoor channel models,
    in Proc. 15th IEEE Int. Work Conf. on Artificial Neural Networks, IWANN 2019. Springer, Gran Canaria, Spain, Jun. 2019, pp. 297–309.
  4. A. Abdelgawwad and M. Pätzold:
    A 3D non-stationary cluster channel model for human activity recognition,
    in Proc. IEEE 89th Veh. Technol. Conf., VTC2019-Spring. Kuala
    Lumpur, Malaysia, Apr./May 2019.
  5. A. Abdelgawwad and M. Pätzold:
    A framework for activity monitoring and fall detection based on the characteristics of indoor channels,
    in Proc. 87th IEEE Veh. Technol. Conf., IEEE VTC2018-Spring. Porto, Portugal, Jun. 2018.
  6. A. Abdelgawwad, M. Pätzold:
    On the influence of walking people on the Doppler spectral characteristics of indoor channels,
    in Proc. IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC´17, Montreal, Canada, Oct. 2017.
    Remark: This paper won the 2017 Excellent Student Paper Award, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC’17) in Montreal, Canada.
  7. A. Abdelgawwad, A. M. Ashour, T. El-Shabrawy and H. Hammad:
    Fast 3D tracing for inddor coverage solutions,
    in Proc. 84th IEEE Vehicular Technology Conference, VTC-Fall 2016, Montreal, Canada, Sep. 2016.

Journals

  1. A. Abdelgawwad, A. Catala, and M. Pätzold:
    A trajectory-driven 3D channel model for human activity recognition,
    IEEE Access, vol. 4, 2021, DOI10.1109/ACCESS.2021.3098951.
  2. R. Hicheri, A. Abdelgawwad, and M. Pätzold,
    A non-stationary relay-based 3D MIMO channel model with time-variant path gains for human activity recognition in indoor environments,
    Annals of Telecommunications, 2021, DOI 10.1107/s12243-021-00844-0.
  3. A. Abdelgawwad, A. Borhani, M. Pätzold:
    Modelling, analysis, and simulation of the micro-Doppler effect in wideband indoor channels with confirmation through pendulum experiments,
    Sensors, vol. 20, no. 4, 2020, DOI 10.3390/s 20041049.