Optimal Routing for Beamforming-Constrained Swarm UAS Networking

With the evolution of 5G cellular communication, beamforming is mature for the implementation on a large scale. The development of cellular networking provides a great opportunity for swarm UAS. Concurrently, the advantages of swarm UAS can provide immense improvement to the advance of industrial and residential implementations. However, the nature of the antenna array constrains beamforming in a limited space which is rarely mentioned in networking routing researches. In this paper, regarding the constrained steering space, we proposed a novel algorithm, Optimized Ad-hoc On-demand Distance Vector (OAODV), which aims to improve the capacity of beamforming on swarm UAS networking. With the adjustable searching space, OAODV can achieve better latency, overhead, and link generation than the conventional algorithms of Ad-hoc On-demand Distance Vector (AODV) and Optimized Link State Routing (OLSR). Compared with AODV and OLSR, OAODV can reduce 35.07% and 68.93% of average overhead, and decrease 47.73% and 11.55% of average latency respectively. Further, we leverage Ant Colony Optimization (ACO) to enhance OAODV, and the ACO enabled OAODV can achieve better throughput and fewer hops with reduction of overhead. The proposed algorithms show the promising capacity to improve swarm UAS networking. The OAODV is more suitable for the 5G cellular networking based swarm UAS networking. The decentralized advantages can improve the deployment of swarm UAS networking on a large scale with more efficiency, flexibility and elasticity.