Rendezvous on the Fly: Efficient Neighbor Discovery for Autonomous UAVs

• Published in: IEEE journal on selected areas in communications Vol. 36; no. 9; pp. 2032 - 2044
• Main Authors: Yang, Bo, Liu, Min, Li, Zhongcheng
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.09.2018; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Ad hoc networks; Algorithms; Anchors; channel hopping sequences; Channels; Clock synchronization; Clocks; Computer simulation; distributed algorithms; Feasibility studies; Flying ad-hoc networks; Heuristic algorithms; neighbor discovery; Prototypes; Rendezvous; Synchronism; Unmanned aerial vehicles; Vehicle dynamics
• ISSN: 0733-8716; 1558-0008
• DOI: 10.1109/JSAC.2018.2864422

Neighbor discovery is a significant communication primitive for adjacent unmanned aerial vehicles (UAVs) to construct a flying ad hoc network (FANET). The multi-channel nature of FANETs makes channel hopping (CH) a feasible rendezvous method for UAVs to hop to the same available channel simultaneously and initiate a connection. However, due to the intrinsic uncoordinated constraints of dispersed UAVs (e.g., lack of clock synchronization, heterogeneous local channels, symmetric roles, and oblivious identifiers), it is challenging to design a performant CH algorithm that can achieve fast neighbor discovery in dynamic FANETs. In this paper, we present a fully uncoordinated matrix-based CH algorithm termed ABIO, which consists of one fixed Anchor column and several variable Binary (i.e., I/O-bit) extended columns in each CH period. The deterministic overlaps as well as the co-primality property of channel numbers among different kinds of columns provide the rendezvous guarantee. Furthermore, for the case with frequently varying channel status, we present a probability-based dynamic discovery (PDD) algorithm. By virtue of the cumulative probability estimation and selection of the qualified channels, the PDD algorithm can achieve timely rendezvous in the unstable environment with high probability. We rigorously analyze the theoretical neighbor discovery latency. We also validate the feasibility and efficiency of the proposed algorithms through extensive simulations. Evaluation results demonstrate the superiority of our algorithms in both stable and unstable communication environments.