2 research outputs found
UAV Communications Based on Non-Orthogonal Multiple Access
This article proposes a novel framework for unmaned aerial vehicle (UAV)
networks with massive access capability supported by non-orthogonal multiple
access (NOMA). In order to better understand NOMA enabled UAV networks, three
case studies are carried out. We first provide performance evaluation of NOMA
enabled UAV networks by adopting stochastic geometry to model the positions of
UAVs and ground users. Then we investigate the joint trajectory design and
power allocation for static NOMA users based on a simplified two-dimensional
(2D) model that UAV is flying around at fixed height. As a further advance, we
demonstrate the UAV placement issue with the aid of machine learning techniques
when the ground users are roaming and the UAVs are capable of adjusting their
positions in three-dimensions (3D) accordingly. With these case studies, we can
comprehensively understand the UAV systems from fundamental theory to practical
implementation
UAV-Enabled Uplink Non-Orthogonal Multiple Access System: Joint Deployment and Power Control
In order to overcome the inherent latency in multi-user unmanned aerial
vehicle (UAV) networks with orthogonal multiple access (OMA). In this paper, we
investigate the UAV enabled uplink non-orthogonal multiple access (NOMA)
network, where a UAV is deployed to collect the messages transmitted by ground
users. In order to maximize the sum rate of all users and to meet the quality
of service (QoS) requirement, we formulate an optimization problem, in which
the UAV deployment position and the power control are jointly optimized. This
problem is non-convex and some variables are binary, and thus it is a typical
NP hard problem. In this paper, an iterative algorithm is proposed with the
assistance of successive convex approximate (SCA) technique and the penalty
function method. In order to reduce the high computational complexity of the
iterative algorithm, a low complexity approximation algorithm is then proposed,
which can achieve a similar performance compared to the iterative algorithm.
Compared with OMA scheme and conventional NOMA scheme, numerical results show
that our proposed algorithms can efficiently improve the sum rate