Safieddin Safavi-Naeini

Atefeh Hajijamali Arani, M. Mahdi Azari, William Melek et al.

Deployment of unmanned aerial vehicles (UAVs) as aerial base stations can deliver a fast and flexible solution for serving varying traffic demand. In order to adequately benefit of UAVs deployment, their efficient placement is of utmost importance, and requires to intelligently adapt to the environment changes. In this paper, we propose a learning-based mechanism for the three-dimensional deployment of UAVs assisting terrestrial cellular networks in the downlink. The problem is modeled as a non-cooperative game among UAVs in satisfaction form. To solve the game, we utilize a low complexity algorithm, in which unsatisfied UAVs update their locations based on a learning algorithm. Simulation results reveal that the proposed UAV placement algorithm yields significant performance gains up to about 52% and 74% in terms of throughput and the number of dropped users, respectively, compared to an optimized baseline algorithm.

Ala Eldin Omer, George Shaker, Safieddin Safavi-Naeini et al.

Microwave sensors are very promising for sensing the blood glucose levels non-invasively for their non-ionizing nature, miniaturized sizing, and low health risks for diabetics. All these features offer the possibility for realizing a portable non-invasive glucose sensor for monitoring glucose levels in real time. In this article, we propose a triple poles complementary split ring resonator (CSRR) produced on a FR4 substrate in microstrip technology in the cm-wave band (1-6 GHz). The proposed bio-sensor can detect the small variations in the dielectric properties (relative permittivity and dielectric losses) of glucose in the blood mimicking aqueous solutions due their intense interaction with the electromagnetic field at harmonic resonances. The resonator exhibits higher sensitivity performance at the different resonances compared to the single and double-poles counterparts as demonstrated by simulations in a 3D full-wave EM solver.