Wireless Broadcast Gossip for Decentralized Drone Swarms: Success Probability, Contraction, and Optimal Aloha

TL;DR

This paper analyzes wireless broadcast gossip in decentralized drone swarms, deriving success probabilities and optimal Aloha parameters, supported by simulations confirming stable operation regions.

Contribution

It provides a tractable baseline model with closed-form success law, contraction bounds, and an interpretable access rule for drone swarm communication.

Findings

Derived a closed-form SIR success law.

Established a mean-square contraction bound.

Confirmed stable operation region via simulations.

Abstract

We study a tractable baseline for average-preserving broadcast gossip in decentralized drone swarms under a quasi-static planar Poisson model and a matching-based abstraction. With slotted Aloha, Rayleigh fading, and threshold decoding, we derive: 1) a closed-form SIR success law; 2) a mean-square contraction bound that separates ideal mixing from wireless successful updates via a conservative lower bound; and 3) a closed-form proxy access rule with interpretable density scaling. Explicit-interference simulations, together with robustness checks for receiver selection, noise, fading, and spatial regularity, confirm a stable intermediate operating region for the Aloha probability.