Accelerating Multi-UAV Collaborative Sensing Data Collection: A Hybrid TDMA-NOMA-Cooperative Transmission in Cell-Free MIMO Networks

TL;DR

This paper proposes a hybrid TDMA-NOMA-cooperative transmission scheme in cell-free MIMO networks to optimize data collection from multiple UAVs, significantly reducing mission completion time.

Contribution

It introduces a novel hybrid transmission strategy combined with task splitting for UAV sensing, optimizing wireless resource utilization in cell-free MIMO networks.

Findings

The proposed scheme reduces sensing mission completion time.

Hybrid TDMA-NOMA improves channel utilization.

Numerical results validate the effectiveness of the approach.

Abstract

This work investigates a collaborative sensing and data collection system in which multiple unmanned aerial vehicles (UAVs) sense an area of interest and transmit images to a cloud server (CS) for processing. To accelerate the completion of sensing missions, including data transmission, the sensing task is divided into individual private sensing tasks for each UAV and a common sensing task that is executed by all UAVs to enable cooperative transmission. Unlike existing studies, we explore the use of an advanced cell-free multiple-input multiple-output (MIMO) network, which effectively manages inter-UAV interference. To further optimize wireless channel utilization, we propose a hybrid transmission strategy that combines time-division multiple access (TDMA), non-orthogonal multiple access (NOMA), and cooperative transmission. The problem of jointly optimizing task splitting ratios and the hybrid TDMA-NOMA-cooperative transmission strategy is formulated with the objective of minimizing mission completion time. Extensive numerical results demonstrate the effectiveness of the proposed task allocation and hybrid transmission scheme in accelerating the completion of sensing missions.