Interference-Aware Queuing Analysis for Distributed Transmission Control in UAV Networks

TL;DR

This work tackles distributed transmission control for UAV networks operating in unlicensed bands by jointly modeling finite queues with delay constraints and in-band interference. It introduces an interference-aware queuing framework and two algorithms, IA-TC and IA-DTC, to optimize channel fading thresholds $\boldsymbol{\beta}$ and maximize the expected throughput $R_n(\boldsymbol{\beta})$, accounting for time-threshold losses $P_n^{dly}$, buffer-overflow losses $P_n^{ov}$, and outage losses $P_n^{out}$. The framework combines coordinate-descent optimization for a single source and consensus-based optimization for distributed nodes, with detailed queueing and outage analyses using Rice/Rayleigh fading and stochastic geometry. Numerical results show IA-TC and IA-DTC achieving higher throughput than baselines, with IA-DTC offering the best performance through joint coordination among all links. The proposed approach provides a principled mechanism to balance queue state and interference in UAV networks, with potential extensions to model-free optimization in dynamic environments.

Abstract

In this paper, we investigate the problem of distributed transmission control for unmanned aerial vehicles (UAVs) operating in unlicensed spectrum bands. We develop a rigorous interference-aware queuing analysis framework that jointly considers two inter-dependent factors: (i) limited-size queues with delay-constrained packet arrival, and (ii) in-band interference introduced by other ground/aerial users. We aim to optimize the expected throughput by jointly analyzing these factors. In the queuing analysis, we explore two packet loss probabilities including, buffer overflow model and time threshold model. For interference analysis, we investigate the outage probability and packet losses due to low signal-to-interference-plus-noise ratio (SINR). We introduce two algorithms namely, Interference-Aware Transmission Control (IA-TC), and Interference-Aware Distributed Transmission Control (IA-DTC). These algorithms maximize the expected throughput by adjusting transmission policies to balance the trade-offs between packet drop from queues vs. transmission errors due to low SINRs. We implement the proposed algorithms and demonstrate that the optimal transmission policy under various scenarios is found.

Figures (7)

• Figure 1: System model that consists of ground and aerial nodes.
• Figure 2: $\beta_n$ vs. # of Iterations by IA-TC
• Figure 3: $R_n$ vs. # of Iterations by IA-TC
• Figure 4: $\beta_n^{\star}$ vs. $\gamma_{th}$ by IA-DTC
• Figure 5: $\beta_i$ vs. Node ID by IA-DTC