Both the unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) are attracting growing attention as enabling technologies for future wireless networks. In particular, IRS-assisted UAV communication, which incorporates IRSs into UAV communications, is emerging to overcome the limitations and problems of UAV communications and improve the system performance. This article aims to provide a comprehensive survey on IRS-assisted UAV communications. We first present six representative scenarios that integrate IRSs and UAVs according to the installation point of IRSs and the role of UAVs. Then, we introduce and discuss the technical features of the state-of-the-art relevant works on IRS-assisted UAV communications systems from the perspective of the main performance criteria, i.e., spectral efficiency, energy efficiency, security, etc. We also introduce machine learning algorithms adopted in the previous works. Finally, we highlight technical issues and research challenges that need to be addressed to realize IRS-assisted UAV communications systems.

Non-orthogonal multiple access (NOMA) is a promising technology for next-generation wireless networks with emerging demands on low latency, high throughput, and massive connectivity. Unlike orthogonal multiple access, NOMA allows multiple users to share the same radio resources, which significantly improves spectral efficiency (SE). To achieve green wireless communications for numerous networked devices, NOMA helps reduce energy consumption while satisfying rate fairness and quality-of-experience requirements. The goal of this paper is to introduce the innovative approaches for NOMA in terms of the SE and energy efficiency, and discuss emerging technologies involved with NOMA. Further, its challenges and future research directions are highlighted.

(D2D) communication has been a potential solution to improve spectral efficiency of cellular systems due to frequency resource sharing. This paper considers D2D communications underlaying an uplink cellular system enabling sparse code multiple access (SCMA) technology, where the base station (BS) can decode the signals of cellular users without mutual interference. The demands for high data rate as well as low latency in a massive connectivity is the main challenging requirement in D2D communications, along with ensuring the quality of service (QoS) for the on-running cellular user equipment (CUEs). To tackle the problem the BS is designed to first assigns the codewords in a codebook to CUEs based on the lower bound of the achievable CUE rates, so that the sum rate (SR) of CUEs is maximized. With the usage of mutual-interference suppression in the SCMA-enabled system, the BS then attempts to maximize the SR of D2Ds in a transmission block through a joint power and resource allocation subject to the QoS requirements for both CUEs and D2Ds. This task is formulated as a mixed-integer non-convex programming.We propose a low-complexity two-phase algorithm of joint heuristic and inner approximation method to efficiently solve the problem. Numerical results verify that the codebook assignment problem based on the lower bound of SR is easily solved, and the proposed algorithm to maximize SR of D2Ds outperforms existing methods.

Spectral efficiency (SE) and energy efficiency (EE) are crucial for next-generation wireless Internet of Things networks. Device-to-device (D2D) communications and sparse code multiple access (SCMA) are promising solutions to meet the high Quality of Service. This requires a proper interference management for an ultradense user system. Considering both resource and power allocation, we herein aim to optimize the SE and improve the EE. First, rate fairness is considered to assign SCMA codewords to both cellular and D2D users. Subsequently, we propose a beamforming design and power allocation algorithm for D2D communications underlaying downlink and uplink operation of cellular networks, wherein energy harvesting is involved as a simultaneous wireless information and power transfer to assist an SCMA network.

This paper considers device-to-device (D2D) communications underlaying an uplink cellular network that adopts sparse code multiple access technology. We aim to maximize the spectral efficiency for D2D links in a transmission block via a joint power and resource allocation subject to the quality-of-service requirements for both cellular user equipments and D2Ds. We propose a low-complexity two-phase algorithm based on heuristic search and inner approximation method to efficiently solve the problem.

The use of transmit beamforming in a radio-frequency wireless power transfer (WPT) system can improve the energy transmission efficiency by concentrating the transmit power in the angle of departure (AoD). Optimal beamforming requires information regarding the AoD or the channel between the transmitter and receiver. A previously proposed WPT system continually estimates the optimal AoD using custom-designed pilot signals, which are known as beam-steered pilot signals and are transmitted periodically at every frame. Herein, we propose a spatio–temporal interpolation technique to improve the accuracy of beam tracking for such a WPT system. Specifically, thin-plate spline interpolation is adopted in the space domain to overcome the limited angular resolution of the beam-steered pilot signals in a three-dimensional channel. In the time domain, polynomial interpolation is performed to track the changing AoD during consecutive frames. Numerical results show that the proposed technique can improve the WPT efficiency as well as the mean square error performance of the beamforming weight vector.