Energy-Efficient Routing Algorithms for UAV-assisted mMTC Networks

Abstract

As one of the three main scenarios of 5G, massive machine-type communications (mMTC) is expected to play an essential role in the future. However, the limited battery of the machine-type communication devices (MTCDs) restricts the network performance. Unmanned aerial vehicles (UAVs) attract more attention recently in cellular networks. The collaboration between the UAV and MTCDs has been a crucial topic to enhance the network performance. In this paper, an adaptive and cost-efficient model is proposed to collect data from MTCDs in a large area assisted by the UAVs. We propose the strategies for higher energy efficiency of MTCDs and longer lifetime of the network based on the model. According to the strategies, we propose a Global Energy-efficient ant colony optimization (ACO) routing algorithm for UAV-assisted mMTC networks (GEAU) to reduce the energy consumption and prolong the lifetime of the networks. Furthermore, in order to reduce the complexity, we propose a practical algorithm with similar performances. Simulations are carried out and illustrate that the proposed algorithms have superior performances compared with existing works.