Performance Analysis and Optimization for the MAC Protocol in UAV-based IoT Network

TL;DR

This paper analyzes and optimizes the uplink MAC protocol in UAV-based IoT networks, addressing communication heterogeneity caused by UAV mobility through a new Markov model and an adaptive CSMA/CA protocol.

Contribution

It introduces a novel performance analysis model considering device clustering and proposes an adaptive CSMA/CA protocol tailored for UAV IoT networks.

Findings

The model accurately predicts throughput under various conditions.

Adaptive protocol improves resource allocation efficiency.

UAV speed and coverage impact network performance significantly.

Abstract

Unmanned aerial vehicles (UAVs) have played an important role in air-ground integration network. Especially in Internet of Things (IoT) services, UAV equipped with communication equipments is widely adopted as a mobile base station (BS) for data collection from IoT devices on the ground. In this paper, we consider an air-ground network in which the UAV flies straightly to collect information from the IoT devices in a 2-D plane based on the CSMA/CA protocol. Due to UAV's continuous mobility, the communication durations of devices in different locations with UAV are not only time-limited, but also vary from each other. To analyze the throughput performance of uplink multiple access control (MAC) protocol, we propose a new analysis model to deal with the communications heterogeneity in the network. Firstly, we divide the devices in the coverage into different clusters according to their communication durations. Then, a quitting probability indicating the probability that a device quits the UAV's coverage at each time slot is clarified. A modified three-dimensional Markov chain model adopting the quitting probability and cluster division is developed for the performance analysis. Besides, we also propose a modified CSMA/CA protocol which fully considers the heterogeneity of the access time and adaptively allocates the time resource among the devices in different clusters. Finally, the effects of retry limit, initial contention window size, the density of the devices, UAVs speed and coverage area are discussed in the simulation section.