Wireless Communications and Control for Swarms of Cellular-Connected UAVs

Abstract

By using wireless connectivity through cellular base stations (BSs), swarms of unmanned aerial vehicles (UAVs) can provide a plethora of services ranging from delivery of goods to surveillance. In particular, UAVs in a swarm can utilize wireless communications to collect information, like velocity and heading angle, from surrounding UAVs for coordinating their operations and maintaining target speed and intra-UAV distance. However, due to the uncertainty of the wireless channel, wireless communications among UAVs will experience a transmission delay which can impair the swarm's ability to stabilize system operation. In this paper, the problem of joint communication and control is studied for a swarm of three cellular-connected UAVs positioned in a triangle formation. In particular, a novel approach is proposed for optimizing the swarm's operation while jointly considering the delay of the wireless network and the stability of the control system. Based on this approach, the maximum allowable delay required to prevent the instability of the swarm is determined. Moreover, by using stochastic geometry, the reliability of the wireless network is derived as the probability of meeting the stability requirement of the control system. The simulation results validate the effectiveness of the proposed joint strategy, and help obtain insightful design guidelines on how to form a stable swarm of UAVs.

Formation of a Wireless Communication System Based on a Swarm of Unmanned Aerial Vehicles

“…The flexible distributed system of a swarm of drones can be part of a traditional communication system, for example, perform the role of a base station node (in the relay mode) in a mobile cellular communication network, a broadband radio access system [28][29][30][31]. Also, on the basis of the swarm can be formed separate relay channels [32] and unique in its purpose combined relay communication systems [33,34].…”

Federated Learning in the Sky: Joint Power Allocation and Scheduling with UAV Swarms

“…Similar to our previous work in [12], we can build a Cartesian coordinate system to capture the locations of UAVs in the swarm, and, then, we decompose the velocity of each UAV into two components, as shown in Fig. 1(b).…”

Skeleton-Based Swarm Routing (SSR): Intelligent Smooth Routing for Dynamic UAV Networks

“…Due to the high cost of deploying GPS and the possibility of losing GPS signals, it uses the received signal strength (RSS) to estimate the distance. The work in [17] solves the problem of communication and control of a triangular swarm of three cellular-connected UAVs and mathematically derives the reliability of the wireless system in terms of meeting the delay requirements. [18] investigates the effect of UAVs sharing the same spectrum with the uplink of cellular users.…”