Channel-Aware Distributed Transmission Control and Video Streaming in UAV Networks

TL;DR

This paper presents a cross-layer framework for optimizing distributed transmission control and video streaming in UAV networks, balancing interference, queue delays, and video quality to improve throughput and PSNR.

Contribution

It introduces the DTC and JDVT-EC algorithms that jointly optimize transmission policies and video encoding rates in UAV networks, a novel cross-layer approach.

Findings

Improves average throughput by up to 51.65% over baselines.

Enhances average PSNR by up to 1.7 dB.

Effectively balances packet loss, interference, and video quality.

Abstract

In this paper, we study the problem of distributed transmission control and video streaming optimization for UAVs operating in unlicensed spectrum bands. We develop a rigorous cross-layer analysis framework that jointly considers three inter-dependent factors: (i) in-band interference introduced by ground-aerial nodes at the physical layer, (ii) limited-size queues with delay-constrained packet arrival at the MAC layer, and (iii) video encoding rate at the application layer. First, we formulate an optimization problem to maximize the average throughput by optimizing the fading threshold. To this end, we jointly analyze the queue-related packet loss probabilities as well as the outage probability due to the low SINR. We introduce the DTC algorithm that maximizes the average throughput by adjusting transmission policies to balance the trade-offs between packet drop from queues vs. transmission errors due to low SINRs. Second, we incorporate the video distortion model to develop distributed PSNR optimization for video streaming. The formulated optimization incorporates two cross-layer parameters, specifically the fading threshold and video encoding rate. To tackle this problem, we develop the JDVT-EC algorithm that enhances the average PSNR for all nodes by fine-tuning transmission policies and video encoding rates to balance the trade-offs between packet loss and lossy video compression distortions. Through extensive numerical analysis, we thoroughly examine the proposed algorithms and demonstrate that they are able to find the optimal transmission policies and video encoding rates under various scenarios. Notably, our approach improves the average throughput by 1.7% to 51.65% compared to various baselines. Additionally, we demonstrate an average PSNR increase of 0.24 dB and 1.7 dB compared to separately optimizing the fading threshold and video encoding rate, respectively.