Throughput Maximization of UAV Networks

Abstract

In this paper we study the deployment of multiple unmanned aerial vehicles (UAVs) to form a temporal UAV network for the provisioning of emergent communications to affected people in a disaster zone, where each UAV is equipped with a lightweight base station device and thus can act as an aerial base station for users. Unlike most existing studies that assumed that a UAV can serve all users in its communication range, we observe that both computation and communication capabilities of a single lightweight UAV are very limited, due to various constraints on its size, weight, and power supply. Thus, a single UAV can only provide communication services to a limited number of users. We study a novel problem of deploying K UAVs in the top of a disaster area such that the sum of the data rates of users served by the UAVs is maximized, subject to that (i) the number of users served by each UAV is no greater than its service capacity; and (ii) the communication network induced by the K UAVs is connected. We then propose a-approximation algorithm for the problem, improving the current best result of the problem by five times (the best approximation ratio so far is)), where e is the base of the natural logarithm. We finally evaluate the algorithm performance via simulation experiments. Experimental results show that the proposed algorithm is very promising. Especially, the solution delivered by the proposed algorithm is up to 12% better than those by existing algorithms.

Adaptive and Fair Deployment Approach to Balance Offload Traffic in Multi-UAV Cellular Networks

“…where Ω is the set of users associated with the -th UAV-BS and ∈ {1, 2, ..., }. According to (9), the data transmission rate of UAV-BS for serving their associated users can be defined by…”

“…In this work, we consider the deployment of multi-UAV-BSs in the target/desired location to improve the energy efficiency of the UAV-BS network. The deployment of UAV-BS must satisfy the predefined minimum data rate requirements (9). Due to the on-board battery capacity of UAVs, hovering, communication equipment, and round-trip recharging waste time and energy.…”

“…Although a single UAV base station shows advantages in improving wireless network performance, this is still limited by size, weight, power consumption (SWaP), and limited computing power, which directly affects the maximum flight altitude, communication coverage, service endurance [6], and capacity [9]. Thus, the service capacity (maximum number of associated users) of each UAV-BS is limited and may not guarantee availability during the entire mission.…”