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Ahmed Abdelmonem Abdelgawwad

Ph.d.-kandidat

 
Kontor:
A2121 ( Jon Lilletuns vei 9, Grimstad )

My research interests and background include network modeling and simulation, channel modeling for fall detection systems, non-stationary channel models, and time-frequency analysis for non-stationary channel models

Faglige interesser

  • Probability Theory and Stochastic Processes

Prosjekter

  • WiCare (A Wireless In-Home Healthcare Monitoring System for Supporting Independent Living or Elderlies)

Vitenskapelige publikasjoner

  • Abdelgawwad, Ahmed; Catala, Andreu; Pätzold, Matthias Uwe (2020). Doppler Power Characteristics Obtained from Calibrated Channel State Information for Human Activity Recognition. IEEE Vehicular Technology Conference (VTC). ISSN: 1090-3038. doi:10.1109/VTC2020-Spring48590.2020.9129187.
  • Abdelgawwad, Ahmed; Borhani, Alireza; Pätzold, Matthias Uwe (2020). Modelling, Analysis, and Simulation of the Micro-Doppler Effect in Wideband Indoor Channels with Confirmation Through Pendulum Experiments. Sensors. ISSN: 1424-8220. 20 (4). doi:10.3390/s20041049.
  • Muaaz, Muhammad; Chelli, Ali; Abdelgawwad, Ahmed; Catala Mallofré, Andreu; Pätzold, Matthias Uwe (2020). WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities. IEEE Access. ISSN: 2169-3536. 8doi:10.1109/ACCESS.2020.3022287.
  • Abdelgawwad, Ahmed; Pätzold, Matthias Uwe (2019). A 3D Non-Stationary Cluster Channel Model for Human Activity Recognition. IEEE Vehicular Technology Conference (VTC). ISSN: 1090-3038. 2019-Aprils 1 - 7. doi:10.1109/VTCSpring.2019.8746345.
  • Muaaz, Muhammad; Abdelgawwad, Ahmed; Pätzold, Matthias Uwe (2019). The Influence of Human Walking Activities on the Doppler Characteristics of Non-stationary Indoor Channel Models. Advances in Computational Intelligence, 15th Int. Work-Conference on Artificial Neural Networks, IWANN 2019, Part I. ISBN: 978-3-030-20520-1. Springer. chapter. s 297 - 309.
  • Abdelgawwad, Ahmed; Pätzold, Matthias Uwe (2018). A Framework for Activity Monitoring and Fall Detection Based on the Characteristics of Indoor Channels. 2018 IEEE 87th Vehicular Technology Conference (VTC Spring). ISBN: 978-1-5386-6355-4. IEEE conference proceedings. chapter.
  • Abdelgawwad, Ahmed; Pätzold, Matthias Uwe (2017). On the influence of walking people on the Doppler spectral characteristics of indoor channels. IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications workshops. ISSN: 2166-9570. doi:10.1109/pimrc.2017.8292482.
  • Abdelgawwad, Ahmed (2019). Monitoring of the Impact of a moving object on the Doppler power characteristics on indoor multipath fading channels.
  • Abdelgawwad, Ahmed; Pätzold, Matthias Uwe (2019). A 3D Non-Stationary Cluster Channel Model for Human Activity Recognition.
  • Abdelgawwad, Ahmed (2018). Modelling the Impact of a Moving Person on the Power Spectrum Characteristics of Indoor Channels.
  • Abdelgawwad, Ahmed; Pätzold, Matthias Uwe (2018). A Framework for Activity Monitoring and Fall Detection Based on the Characteristics of Indoor Channels.

Sist endret: 4.09.2019 12:09