Iman Valiulahi studied his BSc in Electrical Engineering with majors in Electronics at the University of Isfahan, Iran in 2015. He received his MSc in Telecommunication Engineering from Iran University of Science and Technology (IUST), Iran in 2018. He earned the 1st place in his master period. During his master project, he was engaged in a variety of signal processing problems such as super-resolution, one bit
compressed sensing, OFDM radar, and blind deconvolution. The result of these projects was two papers in IEEE Transaction on Signal Processing (one of them is still under major revise) and one paper in IEEE communication letters. The aim of his master study was to show that total-variation norm minimization can be used to detect sparse sources in a continuous dictionary and also is robust against spiky noise. In 2019, he joined University College London (UCL) in the UK, as an early-stage researcher for the European ITN Project PAINLESS, for which he will work on the topic of energy balancing and optimization framework for future energy-neutral HetNets.access points.
Research updates – Period 1
In , we propose a new 3D multi-UAV deployment based on convex optimization where we take co-channel interference into account. To simultaneously take advantage of GPS information and get rid of the non-linear and integer constraints, we propose an algorithm based on the mean-shift technique to find xy-Cartesian coordinate of UAVs and schedule users to UAVs. When users are scheduled and xy locations of UAVs are calculated, we separately optimize UAVs altitudes. Once the placement of UAVs is found, we optimize UAVs transmit powers in a separate block. To jointly optimize UAVs altitudes and transmit powers, an iterative algorithm based on the block coordinate descent is developed. The simulation results are done to investigate the performance of the proposed technique and reveal that our method outperforms the conventional benchmarks CPT and SD-KMVR.
 I. Valiulahi and C. Masouros, “Multi-uav deployment for throughput maximization in the presence of co-channel interference,” IEEE Internet of Things Journal, 2020.
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