Joint Optimization of 3D Placement and Radio Resource Allocation for per-UAV Sum Rate Maximization
Asad Mahmood, Thang X. Vu, Symeon Chatzinotas, Bj\"orn Ottersten

TL;DR
This paper proposes an iterative optimization framework for joint 3D placement and radio resource allocation in multi-UAV OFDMA systems, significantly improving sum-rate performance and interference mitigation.
Contribution
It introduces a decoupled iterative algorithm for joint UAV placement and resource allocation, demonstrating fast convergence and superior sum-rate performance.
Findings
Fast convergence within fewer than 10 iterations
Superior sum-rate compared to existing methods
Optimal power and sub-carrier allocation reduce interference
Abstract
Unmanned aerial vehicles (UAV) have emerged as a practical solution that provides on-demand services to users in areas where the terrestrial network is non-existent or temporarily unavailable, e.g., due to natural disasters or network congestion. In general, UAVs' user-serving capacity is typically constrained by their limited battery life and the finite communication resources that highly impact their performance. This work considers the orthogonal frequency division multiple access (OFDMA) enabled multiple unmanned aerial vehicles (multi-UAV) communication systems to provide on-demand services. The main aim of this work is to derive an efficient technique for the allocation of radio resources, D placement of UAVs, and user association matrices. To achieve the desired objectives, we decoupled the original joint optimization problem into two sub-problems: (i) D placement and user…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsUAV Applications and Optimization · Advanced Wireless Communication Technologies · Satellite Communication Systems
MethodsSPEED: Separable Pyramidal Pooling EncodEr-Decoder for Real-Time Monocular Depth Estimation on Low-Resource Settings
