A Sigmoid-Based Optimization Approach for Multi-UAV-Aided IRS-Assisted Quantum Entanglement Distribution in FSO Networks

Quantum networks connect devices to facilitate the transmission of quantum bits (qubits), harnessing quantum mechanics for groundbreaking telecommunications applications. The quantum state exchange rely on quantum entangled particles which have to be sent from a Quantum Base Station (QBS) to Quantum Nodes (QNs) through an optical channel. Free Space Optical (FSO) links promise flexibility and cost advantages over the classical fiber-based infrastructure. However, the absence of Line of Sight (LoS) between the QBS and QNs may completely disrupt the communication. Therefore, this work focuses on an Intelligent Reflective Surface (IRS)-assisted Unmanned Aerial Vehicle (UAV)-aided FSO quantum network. An optimization problem is formulated to fairly maximize qubit reception at QNs by optimizing UAV hovering locations, constrained by fidelity and link-per-IRS limits. The intractability of the original problem is first tackled with a sigmoid-based approximations, subsequently split into three sub-problems, sequentially solved applying the Successive Convex Approximation (SCA) technique. Numerical results (i) validate the approximation accuracy, and (ii) demonstrates the effectiveness of the proposal against three baseline approaches, showing an order of magnitude increase in terms of fairness.