Abstract
This paper studies the energy efficiency (EE) maximization problem of fixed-wing Unmanned aerial vehicles (UAVs) enabled Internet of Things (IoT) system, where an UAV is employed as an aerial relay with enough cache capacity to amplify and forward (AF) received signals between narrow band (NB)-IoT device and eNodeB. This paper optimizes the unconstrained trajectory of the UAV to maximize the EE of UAV-enabled IoT system to achieve the green communication. Due to the objective function is a fraction and is non-convex, it's hard to solve the optimization problem. Therefore, this paper alternately optimizes trajectory in source subspace and destination subspace with the other fixed and comes up with an algorithm based on successive convex approximation (SCA) method and Dinkelbach method to obtain a local optimal solution. Numerical results show that the proposed UAV trajectory design method can obtain much bigger EE than the running track (RT) trajectory and circular trajectory. Besides, the proposed cache-enabled AF strategy can obtain much bigger EE than non cache-enabled AF strategy.
Highlights
As an emerging network technology and industrial model, the Internet of Things has received extensive attention [1]–[5]
This paper proposes a novel forwarding strategy that the Unmanned aerial vehicles (UAVs) caches received signals from narrow band (NB)-Internet of Things (IoT) device (S) when flies in the source subspace and forwards cached signals to the eNodeB (D) when flies in the destination subspace in order to improve the signal-to-noise ratio (SNR) at the receiver of eNodeB (D)
We propose a two-layer iterative algorithm, in which the outer-layer iteration is based on the Dinkelbach method and the inner-layer iteration algorithm is based on successive convex approximation (SCA) to find the optimal trajectory under given η
Summary
As an emerging network technology and industrial model, the Internet of Things has received extensive attention [1]–[5]. In [18], the authors regarded the UAV as a mobile relay, and optimized the relay transmission power, source transmission power and relay trajectory to maximize communication throughput. The authors in [22] aimed to maximize the throughput of a disaster area UAV communication network by optimizing the position of the UAV. Prior work [29] regarded the UAV as a new mobile user in cellar networks and jointly optimized UAV transmission power and trajectory to maximize the average achievable rate. In [33], the authors employed a fixed-wing UAV unequipped with cache to maximize the end-to-end throughput of AF relaying system. What’s more, this paper considers unconstrained UAV trajectory optimization, which only has fixed initial and final position, to maximize energy efficiency of UAV-enabled IoT system.
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