HSARA: Heuristic Social-Aware Resource Allocation for robust D2D multicasting in UAV-assisted dense 5G networks

The rapid proliferation of smart devices and multimedia-intensive applications poses unprecedented demands on 5G mobile infrastructure, especially when the terrestrial base stations (BS) are unavailable or overwhelmed. When used as an aerial BS, Unmanned Aerial Vehicles (UAVs) offer a compelling and flexible way to restore and improve wireless coverage. In this work, we examine the allocation of social-aware resources for multicast device-to-device (D2D) communications under UAV assisted dense 5G networks, where reducing delays and traffic offloading are the main objectives. The challenge of delays and transmission delays, particularly in emergencies such as natural disasters, that span vast geographical areas, enabling the use of UAVs as scalable on-demand BSs, the density of which can be adjusted proportionally to the network load. A three-dimensional social tie strength model, which jointly captures social overlap (Jaccard similarity of friend sets), similarity of interests (inverse-popularity-weighted content preferences) and contact quality (Gamma-distributed contact duration probability), governs D2D cluster head (CH) selection and resource block (RB) allocation. A scheme of heuristic resource allocation, HSARA (Heuristic Social-Aware Resource Allocation) is proposed to solve the interference management problems intrinsic in the coexistence of D2D clusters and cellular users sharing a common spectrum; the algorithm proceeds through a deferred-acceptance initialization phase and a swap-matching refinement phase and is proven to converge to a stable bilateral exchange matching in a finite number of steps. Simulations are conducted in MATLAB R2020a for a downlink single-cell UAV-assisted dense network in which users are uniformly distributed within a 500 m radius. The proposed HSARA scheme achieves significant throughput gains and nearly quadruples the performance of the social-aware, social-unaware, and MSARA baseline schemes as network density increases, while a non-trivial optimal UAV altitude of 300 m is identified that balances line-of-sight gain against induced interference.