UAV-Assisted Opportunistic Beamforming in Internet of Things Networks

Opportunistic beamforming (OBF) is a promising multiple-input-multiple-output (MIMO) downlink precoding technique, where multiuser diversity gain is achieved to deal with the performance loss caused by low-complexity channel estimation. Due to high-performance and low-complexity channel estimation, OBF is appropriate for Internet of Things (IoT) networks. However, the conventional OBF cannot achieve satisfactory performance in post-disaster communication, and the low signal-to-noise ratio (SNR) makes it hard to establish communication between the base station (BS) and users. Therefore, we propose an unmanned aerial vehicle (UAV)-assisted OBF IoT network (UON) to satisfy the Quality-of-Service (QoS) requirements of users. Then, an optimization problem is formulated to maximize the weighted energy and spectrum efficiencies, while the optimization problem is nonconvex and hard to solve. To obtain the solution, we divide the optimization problem into three suboptimal issues, and then a joint iterative algorithm is applied. According to numerical results, the proposed scheme achieves higher system performances compared with the conventional OBF scheme in both Rayleigh and Rician channels. Moreover, we discuss the objective functions with different weights of spectrum efficiency (SE) and energy efficiency (EE) to adapt the QoS requirements of different scenarios. It is indicated that the proposed scheme can achieve high performance with low computational complexity, regardless of the weighted energy and SE.