Nadia Adem

Ahmed Benfaid, Nadia Adem, Abdurrahman Elmaghbub

Rendering to their abilities to provide ubiquitous connectivity, flexibly and cost effectively, unmanned aerial vehicles (UAVs) have been getting more and more research attention. To take the UAVs' performance to the next level, however, they need to be merged with some other technologies like non-orthogonal multiple access (NOMA) and millimeter wave (mmWave), which both promise high spectral efficiency (SE). As managing UAVs efficiently may not be possible using model-based techniques, another key innovative technology that UAVs will inevitably need to leverage is artificial intelligence (AI). Designing an AI-based technique that adaptively allocates radio resources and places UAVs in 3D space to meet certain communication objectives, however, is a tough row to hoe. In this paper, we propose a neuroevolution of augmenting topologies NEAT framework, referred to as ProSky, to manage NOMA-mmWave-UAV networks. ProSky exhibits a remarkable performance improvement over a model-based method. Moreover, ProSky learns 5.3 times faster than and outperforms, in both SE and energy efficiency EE while being reasonably fair, a deep reinforcement learning DRL based scheme. The ProSky source code is accessible to use here: https://github.com/Fouzibenfaid/ProSky

AbdulMalek Baitulmal, Nadia Adem

Quantum technologies (QT) promise to change the landscape of technologies disruptively in diverse industries. For this reason, many nations around the globe are investing to emerge within the global quantum ecosystem through initiating national programs and international partnerships. Nonetheless, some other countries are still running behind and yet their governments need to take series actions to help their private and public sectors adapt to the looming changes, considering the new regulations required and the huge influence that QT will present in the near future. In this opinion piece, we provide, for the best of our knowledge, the first generally applicable, yet comprehensive and brief, framework for leveraging the emerging quantum technologies to facilitate the establishment of national initiatives properly. The insights presented in this article were driven based on investigating various approaches, initiatives, and roadmaps adopted globally and meeting with local and regional leaders, professionals, and governmental officials. Furthermore, taken into account socioeconomic and institutional dimensions of the Libyan society, we project the framework for the Libyan nation. This opinion piece is intended to inspire researchers, technical industrial experts, stakeholders, and governmental bodies to find roles they need to play to bring QT forward.

Ahmed M. Badi, Taissir Y. Elganimi, Osama A. S. Alkishriwo et al.

In this paper, deep neural network (DNN) is integrated with spatial modulation-orthogonal frequency division multiplexing (SM-OFDM) technique for end-to-end data detection over Rayleigh fading channel. This proposed system directly demodulates the received symbols, leaving the channel estimation done only implicitly. Furthermore, an ensemble network is also proposed for this system. Simulation results show that the proposed DNN detection scheme has a significant advantage over classical methods when the pilot overhead and cyclic prefix (CP) are reduced, owing to its ability to learn and adjust to complicated channel conditions. Finally, the ensemble network is shown to improve the generalization of the proposed scheme, while also showing a slight improvement in its performance.